Uses of Class
jline.util.matrix.Matrix

Packages that use Matrix

Package	Description
jline.api.aoi	Age of Information (AoI) analysis algorithms.
jline.api.cache	Cache modeling algorithms and performance analysis methods.
jline.api.fes
jline.api.fj
jline.api.lossn	APIs for stochastic models of loss networks and blocking systems.
jline.api.lsn	Layered Stochastic Network (LSN) algorithms.
jline.api.mam	Matrix Analytic Methods (MAM) for structured Markov chains.
jline.api.mam.m3pp	Marked Markov-Modulated Poisson Process (M3PP) manipulation and fitting.
jline.api.map
jline.api.mapqn	MAP queueing network analysis algorithms.
jline.api.mc	Markov Chain analysis algorithms.
jline.api.measures	Statistical measures and distance metrics.
jline.api.nc
jline.api.npfqn	Non-Product Form Queueing Network algorithms.
jline.api.pfqn	Product-Form Queueing Network (PFQN) analysis algorithms.
jline.api.pfqn.lcfs
jline.api.pfqn.ld	Load-dependent Product Form Queueing Network algorithms.
jline.api.pfqn.mva	Mean Value Analysis algorithms for Product Form Queueing Networks.
jline.api.pfqn.nc	Normalizing constant algorithms for Product Form Queueing Networks.
jline.api.qsys	Queueing system analysis algorithms.
jline.api.rl
jline.api.sn	Stochastic network analysis utilities.
jline.api.trace	Trace analysis algorithms for empirical data.
jline.api.wf	Workflow analysis algorithms.
jline.bench	Benchmarking utilities and performance test models for LINE solvers.
jline.examples	Comprehensive examples and tutorials for LINE queueing network modeling.
jline.gen
jline.inference.api
jline.inference.lang
jline.inference.util
jline.io	Input/output from the command line or XML files.
jline.io.tikz	TikZ visualization package for LINE queueing networks.
jline.lang	Abstractions to declare basic elements of a model.
jline.lang.layered	This package contains the classes used the specify LayeredNetwork objects
jline.lang.nodeparam	Node parameter specifications and configuration classes.
jline.lang.nodes	This package contains the classes used the specify Network objects
jline.lang.processes	This package contains processes and statistical distributions used to specify arrival rates, service rates, and item popularities
jline.lang.reward	Reward function types and utilities for CTMC analysis.
jline.lang.sections	Classes that model the individual sections that form a Network node
jline.lang.state	Classes that model the state of a network and its individual nodes
jline.lang.workflow
jline.lib.butools	Port of BuTools library for phase-type distributions and MAP processes.
jline.lib.butools.dmap
jline.lib.butools.dph	Package containing Discrete Phase-Type (DPH) distribution functions.
jline.lib.butools.fitting	Package containing trace fitting utility functions.
jline.lib.butools.mam	Package containing Matrix-Analytic Methods (MAM) solvers.
jline.lib.butools.map	Package containing Markovian Arrival Process (MAP) functions.
jline.lib.butools.mc	Package containing Markov chain validation and solving functions.
jline.lib.butools.ph	Package containing phase-type distribution functions.
jline.lib.butools.queues
jline.lib.butools.reptrans	Package containing representation transformation functions.
jline.lib.butools.trace	Package containing trace analysis functions.
jline.lib.fjcodes
jline.lib.kpctoolbox	Port of the KPC-Toolbox library for Markovian process fitting and manipulation.
jline.lib.kpctoolbox.aph
jline.lib.kpctoolbox.basic
jline.lib.kpctoolbox.mc
jline.lib.kpctoolbox.mvph
jline.lib.kpctoolbox.smp
jline.lib.m3a	Port of M3A library for matrix-based moment matching approximation algorithms.
jline.lib.perm	Port of permanent computation algorithms for matrix permanents.
jline.lib.qmam
jline.lib.smc	Port of SMC library for structured Markov chain analysis algorithms.
jline.solvers	Solver superclasses and related data structures.
jline.solvers.auto	Automatic solver selection and configuration for queueing networks.
jline.solvers.ctmc	This package provides an implementation of SolverCTMC.
jline.solvers.ctmc.analyzers	Analyzers for SolverCTMC.
jline.solvers.ctmc.handlers	Handlers for SolverCTMC.
jline.solvers.env	This package provides an implementation of SolverENV (ENV).
jline.solvers.fluid	This package provides an implementation of SolverFluid (FLD).
jline.solvers.fluid.analyzers	Analyzers for SolverFluid.
jline.solvers.fluid.handlers	Handlers for SolverFluid.
jline.solvers.jmt	This package provides an implementation of SolverJMT.
jline.solvers.jmt.io
jline.solvers.ldes	LINE Discrete Event Simulator (LDES) solver using SSJ library.
jline.solvers.ln	This package provides an implementation of SolverLN.
jline.solvers.mam	This package provides an implementation of SolverMAM.
jline.solvers.mam.handlers	Handlers for SolverMAM.
jline.solvers.mva	This package provides an implementation of SolverMVA.
jline.solvers.mva.handlers	Handlers for SolverMVA.
jline.solvers.nc	This package provides an implementation of SolverNC.
jline.solvers.qns	This package provides an implementation of SolverQNS.
jline.solvers.ssa	This package provides an implementation of SolverSSA.
jline.solvers.ssa.analyzers	Analyzers for SolverSSA.
jline.solvers.ssa.handlers	Handlers for SolverSSA.
jline.streaming
jline.util	Fundamental data structures and utilities
jline.util.graph	Graph theory utilities and algorithms for network analysis.
jline.util.matrix	Matrix operations and linear algebra utilities for queueing analysis.

Uses of Matrix in jline.api.aoi

Methods in jline.api.aoi that return Matrix

Modifier and Type	Method	Description
Matrix	Aoi_dist2phResult.component1()
Matrix	Aoi_dist2phResult.component2()
Matrix	Aoi_dist2phResult.getAlpha()
Matrix	AoiMfqResult.getAoiA()
Matrix	AoiMfqResult.getAoiG()
Matrix	AoiMfqResult.getAoiH()
Matrix	AoiMfqResult.getPaoiA()
Matrix	AoiMfqResult.getPaoiG()
Matrix	AoiMfqResult.getPaoiH()
Matrix	AoiParams.getS()
Matrix	AoiParams.getSigma()
Matrix	Aoi_dist2phResult.getT()
Matrix	AoiParams.getT()
Matrix	AoiParams.getTau()

Methods in jline.api.aoi with parameters of type Matrix

Modifier and Type	Method	Description
static LstFunction	Aoi_lst.aoi_lst_ph(Matrix alpha, Matrix T)	LST for phase-type distribution: H*(s) = alpha * (s*I - T)^{-1} * (-T * e)
static AoiMfqResult	Aoi_solve_bufferless.aoi_solve_bufferless(Matrix tau, Matrix T, Matrix sigma, Matrix S, double p)	Solve bufferless (PH/PH/1/1 or PH/PH/1/1*) AoI system using MFQ.
static AoiMfqResult	Aoi_solve_singlebuffer.aoi_solve_singlebuffer(double lambda, Matrix sigma, Matrix S, double r)

Constructors in jline.api.aoi with parameters of type Matrix

Modifier	Constructor	Description
	Aoi_dist2phResult(Matrix alpha, Matrix T)
	AoiMfqResult(Matrix aoiG, Matrix aoiA, Matrix aoiH, double aoiMean, double aoiVar, Matrix paoiG, Matrix paoiA, Matrix paoiH, double paoiMean, double paoiVar, String systemType, double preemption)
	AoiParams(Matrix tau, Matrix T, Matrix sigma, Matrix S, double p, double lambda, double r, String systemType, String arrivalType)

Uses of Matrix in jline.api.cache

Fields in jline.api.cache declared as Matrix

Modifier and Type	Field	Description
final Matrix	CacheMissFpiResult.MI
final Matrix	CacheMissFpiResult.MU
final Matrix	Cache_miss.CacheMissResult.perItemMissProb
final Matrix	Cache_miss.CacheMissResult.perItemMissRate
final Matrix	Cache_miss.CacheMissResult.perUserMissRate
final Matrix	CacheMissFpiResult.pi0

Methods in jline.api.cache that return Matrix

Modifier and Type	Method	Description
static Matrix	Cache_erec.cache_erec(Matrix gamma, Matrix m)	Computes the cache miss rate using an exact recursive method.
static Matrix	Cache_erec.cache_erec_aux(Matrix gamma, Matrix m, int k)	Auxiliary method for computing the cache miss rate using an exact recursive method.
static Matrix	Cache_prob_erec.cache_prob_erec(Matrix gamma, Matrix m)	Computes the cache state probabilities using an exact recursive method.
static Matrix	Cache_prob_fpi.cache_prob_fpi(Matrix gamma, Matrix m)	Estimate asymptotic values of the cache state probabilities at steady-state.
static Matrix	Cache_prob_is.cache_prob_is(Matrix gamma, Matrix m)
static Matrix	Cache_prob_is.cache_prob_is(Matrix gamma, Matrix m, int samples)	Computes cache hit probabilities using Monte Carlo importance sampling.
static Matrix	Cache_prob_rayint.cache_prob_rayint(Matrix gamma, Matrix m)	Computes the cache state probabilities using the ray method.
static Matrix	Cache_prob_spm.cache_prob_spm(Matrix gamma, Matrix m)	Computes the cache state probabilities using the ray method.
static Matrix	Cache_rrm_meanfield_ode.cache_rrm_meanfield_ode(Matrix x, Matrix lambda, Matrix m, int n, int h)	ODE system for RRM (Random Replacement Model) mean field equations.
static Matrix	Cache_t_hlru.cache_t_hlru(Matrix gamma, Matrix m)	Computes the characteristic time of each list in the TTL approximation of h-LRU.
static Matrix	Cache_t_hlru.cache_t_hlru_aux(double[] x, Matrix gamma, Matrix m, int n, int h)	Auxiliary function for cache_t_hlru inner optimization.
static Matrix	Cache_t_lrum.cache_t_lrum(Matrix gamma, Matrix m)	Computes the characteristic time of each list in the TTL approximation of LRU(m).
static Matrix	Cache_t_lrum.cache_t_lrum_aux(double[] x, Matrix gamma, Matrix m, int n, int h)	Auxiliary function for cache_t_lrum inner optimization.
static Matrix	Cache_t_lrum_map.cache_t_lrum_map(MatrixCell[] D0, MatrixCell[] D1, Matrix m)
static Matrix	Cache_ttl_hlru.cache_ttl_hlru(Matrix[] lambda, Matrix m)	Solve hierarchical least-recently-used caches h-LRU using the TTL approximation.
static Matrix	Cache_ttl_lrua.cache_ttl_lrua(Matrix[] lambda, Matrix[][] R, Matrix m)	Solve arbitrary replacement policy caches LRU(A) using the TTL tree approximation.
static Matrix	Cache_ttl_lrum.cache_ttl_lrum(Matrix[] gamma, Matrix m)	Solve multi-list least-recently-used caches LRU(m) using the TTL approximation.
static Matrix	Cache_ttl_tree.cache_ttl_tree(Matrix[] lambda, Matrix[][] R, Matrix m)
static Matrix	Cache_ttl_tree.cache_ttl_tree(Matrix[] lambda, Matrix[][] R, Matrix m, Long seed)
static Matrix	Cache_xi_bvh.cache_xi_bvh(Matrix gamma, Matrix m)	Computes the cache xi terms using the iterative method used in Gast-van Houdt, SIGMETRICS 2015.
static Matrix	Cache_xi_iter.cache_xi_iter(Matrix gamma, Matrix m)	Computes the cache xi terms using the iterative method (Gast-van Houdt, SIGMETRICS 2015).
Matrix	CacheMissFpiResult.getMI()
Matrix	CacheMissFpiResult.getMU()
Matrix	CacheMissFpiResult.getPi0()
static Matrix	Cache_t_hlru.hlruTime(double[] x, Matrix gamma, Matrix m, int n, int h)
static Matrix	Cache_t_lrum_map.lrummapTime(double[] x, MatrixCell[] D0Matrix, MatrixCell[] D1Matrix, Matrix m, int n, int h)

Methods in jline.api.cache that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Double,Matrix>	Cache_mva_miss.cache_mva_miss(Matrix p, Matrix m, Matrix R)	Compute cache miss probabilities using Mean Value Analysis approach.

Methods in jline.api.cache with parameters of type Matrix

Modifier and Type	Method	Description
static Matrix	Cache_erec.cache_erec(Matrix gamma, Matrix m)	Computes the cache miss rate using an exact recursive method.
static Matrix	Cache_erec.cache_erec_aux(Matrix gamma, Matrix m, int k)	Auxiliary method for computing the cache miss rate using an exact recursive method.
static Ret.cacheGamma	Cache_gamma_lp.cache_gamma_lp(Matrix[] lambda, Matrix[][] R)	Computes access factors for the cache.
static Ret.cacheIs	Cache_is.cache_is(Matrix gamma, Matrix m)
static Ret.cacheIs	Cache_is.cache_is(Matrix gamma, Matrix m, int samples)	Estimate the normalizing constant of the cache steady state distribution using Monte Carlo importance sampling.
static Cache_miss.CacheMissResult	Cache_miss.cache_miss(Matrix gamma, Matrix m)
static Cache_miss.CacheMissResult	Cache_miss.cache_miss(Matrix gamma, Matrix m, Matrix lambda)
static double	Cache_miss_asy.cache_miss_asy(Matrix gamma, Matrix m)
static double	Cache_miss_asy.cache_miss_asy(Matrix gamma, Matrix m, int maxIter, double tolerance)	Compute cache miss rates using asymptotic approximation (Fixed Point Iteration method).
static CacheMissFpiResult	Cache_miss_fpi.cache_miss_fpi(Matrix gamma, Matrix m)
static CacheMissFpiResult	Cache_miss_fpi.cache_miss_fpi(Matrix gamma, Matrix m, MatrixCell lambda)	Compute cache miss rates using Fixed Point Iteration (FPI) method.
static Ret.cacheMissSpm	Cache_miss_is.cache_miss_is(Matrix gamma, Matrix m, MatrixCell lambda)
static Ret.cacheMissSpm	Cache_miss_is.cache_miss_is(Matrix gamma, Matrix m, MatrixCell lambda, int samples)	Computes cache miss rates using Monte Carlo importance sampling.
static Ret.cacheMissSpm	Cache_miss_rayint.cache_miss_rayint(Matrix gamma, Matrix m, MatrixCell lambda)	Estimates the cache miss rate and related metrics using the ray method for PDEs.
static Ret.cacheMissSpm	Cache_miss_spm.cache_miss_spm(Matrix gamma, Matrix m, MatrixCell lambda)
static Ret.cacheMVA	Cache_mva.cache_mva(Matrix gamma, Matrix m)	Exact recursive solution of the caching model.
static Pair<Double,Matrix>	Cache_mva_miss.cache_mva_miss(Matrix p, Matrix m, Matrix R)	Compute cache miss probabilities using Mean Value Analysis approach.
static ArrayList<Integer>	Cache_gamma_lp.cache_par(Matrix R, int j)	Finds the parent of a given list index.
static Matrix	Cache_prob_erec.cache_prob_erec(Matrix gamma, Matrix m)	Computes the cache state probabilities using an exact recursive method.
static Matrix	Cache_prob_fpi.cache_prob_fpi(Matrix gamma, Matrix m)	Estimate asymptotic values of the cache state probabilities at steady-state.
static Matrix	Cache_prob_is.cache_prob_is(Matrix gamma, Matrix m)
static Matrix	Cache_prob_is.cache_prob_is(Matrix gamma, Matrix m, int samples)	Computes cache hit probabilities using Monte Carlo importance sampling.
static Matrix	Cache_prob_rayint.cache_prob_rayint(Matrix gamma, Matrix m)	Computes the cache state probabilities using the ray method.
static Matrix	Cache_prob_spm.cache_prob_spm(Matrix gamma, Matrix m)	Computes the cache state probabilities using the ray method.
static Ret.cacheSpm	Cache_rayint.cache_rayint(Matrix gamma, Matrix m)	Approximate the normalizing constant of the cache steady state distribution using the ray method.
static Matrix	Cache_rrm_meanfield_ode.cache_rrm_meanfield_ode(Matrix x, Matrix lambda, Matrix m, int n, int h)	ODE system for RRM (Random Replacement Model) mean field equations.
static Ret.cacheSpm	Cache_spm.cache_spm(Matrix gamma, Matrix m)	Approximate the normalizing constant of the cache steady state distribution using the SPM method.
static Matrix	Cache_t_hlru.cache_t_hlru(Matrix gamma, Matrix m)	Computes the characteristic time of each list in the TTL approximation of h-LRU.
static Matrix	Cache_t_hlru.cache_t_hlru_aux(double[] x, Matrix gamma, Matrix m, int n, int h)	Auxiliary function for cache_t_hlru inner optimization.
static Matrix	Cache_t_lrum.cache_t_lrum(Matrix gamma, Matrix m)	Computes the characteristic time of each list in the TTL approximation of LRU(m).
static Matrix	Cache_t_lrum.cache_t_lrum_aux(double[] x, Matrix gamma, Matrix m, int n, int h)	Auxiliary function for cache_t_lrum inner optimization.
static Matrix	Cache_t_lrum_map.cache_t_lrum_map(MatrixCell[] D0, MatrixCell[] D1, Matrix m)
static Matrix	Cache_ttl_hlru.cache_ttl_hlru(Matrix[] lambda, Matrix m)	Solve hierarchical least-recently-used caches h-LRU using the TTL approximation.
static Matrix	Cache_ttl_lrua.cache_ttl_lrua(Matrix[] lambda, Matrix[][] R, Matrix m)	Solve arbitrary replacement policy caches LRU(A) using the TTL tree approximation.
static Matrix	Cache_ttl_lrum.cache_ttl_lrum(Matrix[] gamma, Matrix m)	Solve multi-list least-recently-used caches LRU(m) using the TTL approximation.
static double	Cache_ttl_lrum_map.cache_ttl_lrum_map(MatrixCell[] D0Matrix, MatrixCell[] D1Matrix, Matrix m)
static Matrix	Cache_ttl_tree.cache_ttl_tree(Matrix[] lambda, Matrix[][] R, Matrix m)
static Matrix	Cache_ttl_tree.cache_ttl_tree(Matrix[] lambda, Matrix[][] R, Matrix m, Long seed)
static Matrix	Cache_xi_bvh.cache_xi_bvh(Matrix gamma, Matrix m)	Computes the cache xi terms using the iterative method used in Gast-van Houdt, SIGMETRICS 2015.
static Ret.cacheXiFp	Cache_xi_fp.cache_xi_fp(Matrix gamma, Matrix m, Matrix xi)
static Matrix	Cache_xi_iter.cache_xi_iter(Matrix gamma, Matrix m)	Computes the cache xi terms using the iterative method (Gast-van Houdt, SIGMETRICS 2015).
static Matrix	Cache_t_hlru.hlruTime(double[] x, Matrix gamma, Matrix m, int n, int h)
static Matrix	Cache_t_lrum_map.lrummapTime(double[] x, MatrixCell[] D0Matrix, MatrixCell[] D1Matrix, Matrix m, int n, int h)

Constructors in jline.api.cache with parameters of type Matrix

Modifier	Constructor	Description
	CacheMissFpiResult(double M, Matrix MU, Matrix MI, Matrix pi0)
	CacheMissResult(double globalMissRate, Matrix perUserMissRate, Matrix perItemMissRate, Matrix perItemMissProb)

Uses of Matrix in jline.api.fes

Fields in jline.api.fes declared as Matrix

Modifier and Type	Field	Description
final Matrix	FESDeaggInfo.cutoffs
final Matrix	FESDeaggInfo.stochCompComplement
final Matrix	FESDeaggInfo.stochCompSubset

Fields in jline.api.fes with type parameters of type Matrix

Modifier and Type	Field	Description
final List<Matrix>	FESDeaggInfo.throughputTable

Methods in jline.api.fes that return Matrix

Modifier and Type	Method	Description
Matrix	FESDeaggInfo.getCutoffs()
Matrix	FESOptions.getCutoffs()	Per-class population cutoffs (default: null, uses total jobs per class).
Matrix	FESDeaggInfo.getStochCompComplement()
Matrix	FESDeaggInfo.getStochCompSubset()

Methods in jline.api.fes that return types with arguments of type Matrix

Modifier and Type	Method	Description
List<Matrix>	FESDeaggInfo.getThroughputTable()

Methods in jline.api.fes with parameters of type Matrix

Modifier and Type	Method	Description
static FESOptions	FESOptions.withCutoffs(Matrix cutoffs)	Create options with specified cutoffs.

Constructors in jline.api.fes with parameters of type Matrix

Modifier	Constructor	Description
	FESDeaggInfo(Network originalModel, List<Station> stationSubset, int[] subsetIndices, int[] complementIndices, List<Matrix> throughputTable, Matrix cutoffs, Matrix stochCompSubset, Matrix stochCompComplement, Network isolatedModel, int fesNodeIdx)
	FESOptions(String solver, Matrix cutoffs, boolean verbose)

Uses of Matrix in jline.api.fj

Methods in jline.api.fj with parameters of type Matrix

Modifier and Type	Method	Description
static FJArrival	FJConvert.convertToFJArrival(Matrix D0, Matrix D1)	Convert LINE MAP to FJ arrival format
static FJService	FJConvert.convertToFJService(Matrix S, Matrix s, Matrix tau)	Convert LINE PH to FJ service format

Uses of Matrix in jline.api.lossn

Methods in jline.api.lossn with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.lossnErlangFP	Lossn_erlangfp.lossn_erlangfp(Matrix nuVec, Matrix Amat, Matrix cVec)	Erlang fixed point approximation for loss networks.

Uses of Matrix in jline.api.lsn

Methods in jline.api.lsn that return Matrix

Modifier and Type	Method	Description
static Matrix	LsnMaxMultiplicity.lsnMaxMultiplicity(LayeredNetworkStruct lsn)	Computes the maximum multiplicity that can be sustained by each task.

Uses of Matrix in jline.api.mam

Fields in jline.api.mam declared as Matrix

Modifier and Type	Field	Description
final Matrix	Qbd_bmapbmap1.QbdBmapResult.A_1
final Matrix	Qbd_bmapbmap1.QbdBmapResult.A0
final Matrix	Qbd_rg.QbdRgResult.B
final Matrix	Qbd_bmapbmap1.QbdBmapResult.B0
final Matrix	Qbd_rg.QbdRgResult.F
final Matrix	Mamap2m_coefficients.Mamap2mCoefficients.first
final Matrix	Qbd_rg.QbdCrResult.G
final Matrix	Qbd_rg.QbdRgResult.G
final Matrix	Qbd_rg.QbdRgResult.L
final Matrix	Qbd_rg.QbdCrResult.R
final Matrix	Qbd_rg.QbdRgResult.R
final Matrix	Mamap2m_coefficients.Mamap2mCoefficients.second
final Matrix	Mamap2m_coefficients.Mamap2mCoefficients.third
final Matrix	Qbd_rg.QbdCrResult.U
final Matrix	Qbd_rg.QbdRgResult.U

Fields in jline.api.mam with type parameters of type Matrix

Modifier and Type	Field	Description
final List<Matrix>	Qbd_bmapbmap1.QbdBmapResult.A1
final List<Matrix>	Qbd_bmapbmap1.QbdBmapResult.B1

Methods in jline.api.mam that return Matrix

Modifier and Type	Method	Description
Matrix	Qbd_rg.QbdRgResult.component1()
Matrix	LdqbdResult.component2()
Matrix	Qbd_rg.QbdRgResult.component2()
Matrix	Qbd_rg.QbdRgResult.component3()
Matrix	Qbd_rg.QbdRgResult.component4()
Matrix	Qbd_rg.QbdRgResult.component5()
Matrix	Qbd_rg.QbdRgResult.component6()
static Matrix	Dmap_pie.dmap_pie(MatrixCell DMAP)
static Matrix	Dmap_pie.dmap_pie(Matrix D0, Matrix D1)	Computes the stationary vector at arrival epochs of a discrete-time MAP.
Matrix	QbdMapMap1Result.getA_1()
Matrix	QbdMapMap1Result.getA0()
Matrix	QbdMapMap1Result.getA1()
Matrix	QbdRapRap1Result.getB()
Matrix	QbdMapMap1Result.getEta()
Matrix	QbdRapRap1Result.getEta()
Matrix	QbdRapRap1Result.getF()
Matrix	QbdMapMap1Result.getG()
Matrix	QbdRapRap1Result.getG()
Matrix	QbdRapRap1Result.getL()
Matrix	LdqbdResult.getPi()
Matrix	QbdMapMap1Result.getPqueue()
Matrix	QbdRapRap1Result.getPqueue()
Matrix	QbdMapMap1Result.getR()
Matrix	QbdRapRap1Result.getR()
Matrix	QbdMapMap1Result.getU()
static Matrix[]	Mamap2m_fit.mamap2m_fit(double M1, double M2, double M3, double GAMMA, double[] P, double[] F, double[] B, Matrix S)
static Matrix[]	Mamap2m_fit.mamap2m_fit(double M1, double M2, double M3, double GAMMA, double[] P, double[] F, double[] B, Matrix S, double[] fbsWeights)
static Matrix	Map_acf.map_acf(MatrixCell MAP)
static Matrix	Map_acf.map_acf(MatrixCell MAP, Matrix lags)
static Matrix	Map_acf.map_acf(Matrix D0, Matrix D1)
static Matrix	Map_acf.map_acf(Matrix D0, Matrix D1, int lag)
static Matrix	Map_acf.map_acf(Matrix D0, Matrix D1, Matrix lags)	Computes the autocorrelation function (ACF) for a given MAP at multiple lags.
static Matrix[]	Map_block.map_block(double E1, double E2, double E3, double G2)
static Matrix[]	Map_block.map_block(double E1, double E2, double E3, double G2, String OPT)	Constructs a MAP(2) or MAP(1) according to given moments and autocorrelation parameters.
static Matrix	Map_cdf.map_cdf(MatrixCell MAP, Matrix points)	CDF of MAP inter-arrival times when MAP is a MatrixCell.
static Matrix	Map_cdf.map_cdf(Matrix D0, Matrix D1, Matrix points)	Computes the cumulative distribution function (CDF) of the inter-arrival times of a Markovian Arrival Process (MAP).
static Matrix	Map_embedded.map_embedded(MatrixCell MAP)	Computes the embedded discrete-time Markov chain (DTMC) matrix of a MAP given as a MatrixCell.
static Matrix	Map_embedded.map_embedded(Matrix D0, Matrix D1)	Computes the embedded discrete-time Markov chain (DTMC) matrix of a MAP.
static Matrix[]	Map_feasblock.map_feasblock(double E1, double E2, double E3, double G2)
static Matrix[]	Map_feasblock.map_feasblock(double E1, double E2, double E3, double G2, String OPT)	Fits the most similar feasible MAP when exact moment matching fails.
static Matrix	Map_infgen.map_infgen(MatrixCell MAP)	Computes the infinitesimal generator matrix (Q) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static Matrix	Map_infgen.map_infgen(Matrix D0, Matrix D1)	Computes the infinitesimal generator matrix (Q) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static Matrix[]	Map_kpc.map_kpc(List<Matrix[]> maps)	Convenience function for composing a list of MAPs.
static Matrix[]	Map_kpc.map_kpc(Matrix[] MAPa, Matrix[] MAPb)	Convenience function for composing exactly two MAPs.
static Matrix	Map_pie.map_pie(MatrixCell MAP)	Computes the steady-state probability vector of the embedded DTMC of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static Matrix	Map_pie.map_pie(Matrix D0, Matrix D1)	Computes the steady-state probability vector of the embedded Discrete Time Markov Chain (DTMC) associated with a Markovian Arrival Process (MAP).
static Matrix	Map_piq.map_piq(MatrixCell MAP)	Computes the steady-state vector (pi) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static Matrix	Map_piq.map_piq(Matrix D0, Matrix D1)	Computes the steady-state vector (pi) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static Matrix	Map_pntiter.map_pntiter(Matrix[] MAP, int na, double t)
static Matrix	Map_pntiter.map_pntiter(Matrix[] MAP, int na, double t, Integer M)	Probability of having exactly na arrivals within time interval t using iterative method.
static Matrix	Map_prob.map_prob(MatrixCell MAP)	Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
static Matrix	Map_prob.map_prob(Matrix D0, Matrix D1)	Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
static Matrix	Map_varcount.map_varcount(MatrixCell MAP, Matrix t)
static Matrix	Map_varcount.map_varcount(Matrix D0, Matrix D1, Matrix t)	Variance of the counts in a MAP over multiple time periods.
static Matrix	Me_pie.me_pie(MatrixCell ME)	Computes the stationary initial probability for an ME/RAP distribution using matrices stored in a MatrixCell.
static Matrix	Me_pie.me_pie(Matrix H0, Matrix H1)	Computes the stationary initial probability for an ME/RAP distribution.
static Matrix	Mmap_backward_moment.mmap_backward_moment(MatrixCell MMAP, Matrix ORDERS)
static Matrix	Mmap_backward_moment.mmap_backward_moment(MatrixCell MMAP, Matrix ORDERS, int NORM)	Computes the backward moments of an MMAP for specified orders with normalization.
static Matrix[]	Mmap_compress.mmap_compress(Matrix[] mmap)
static Matrix[]	Mmap_compress.mmap_compress(Matrix[] mmap, String method)
static Matrix	Mmap_count_idc.mmap_count_idc(MatrixCell MMAP, double t)	Computes the index of dispersion for counts (IDC) for a Markovian Arrival Process with marked arrivals (MMAP) over a time period.
static Matrix	Mmap_count_lambda.mmap_count_lambda(MatrixCell mmap)	Computes the arrival rate vector of the counting process for the given Marked MAP (MMAP).
static Matrix	Mmap_count_mcov.mmap_count_mcov(Matrix[] mmap, double t)	Array-based overload.
static Matrix	Mmap_count_mcov.mmap_count_mcov(MatrixCell MMAP, double t)	Computes the count covariance between each pair of classes at a given time scale.
static Matrix	Mmap_count_mean.mmap_count_mean(MatrixCell MMAP, double t)	Computes the mean count vector of events of different types in a Markovian Arrival Process with marked arrivals (MMAP) over a time period.
static Matrix	Mmap_count_var.mmap_count_var(MatrixCell MMAP, double t)	Computes the variance of the count vector of events of different types in a MMAP over a time period.
static Matrix	Mmap_cross_moment.mmap_cross_moment(MatrixCell mmap, int k)	Computes the k-th cross-moment matrix for a given MMAP.
static Matrix	Mmap_embedded.mmap_embedded(MatrixCell mmap)	Computes the embedded chain of an MMAP.
static Matrix	Mmap_forward_moment.mmap_forward_moment(MatrixCell MMAP, Matrix ORDERS)
static Matrix	Mmap_forward_moment.mmap_forward_moment(MatrixCell MMAP, Matrix ORDERS, int NORM)	Computes the forward moments of an MMAP for specified orders with normalization.
static Matrix	Mmap_idc.mmap_idc(MatrixCell MMAP)	Computes the asymptotic index of dispersion for counts (IDC) for a Markovian Arrival Process with marked arrivals (MMAP).
static Matrix	Mmap_lambda.mmap_lambda(MatrixCell MMAP)	Alias for mmap_count_lambda.
static Matrix	Mmap_pc.mmap_pc(MatrixCell MMAP)	Computes the proportion of counts (PC) for each type in a Markovian Arrival Process with marked arrivals (MMAP).
static Matrix	Mmap_pie.mmap_pie(Matrix[] mmap)
static Matrix	Mmap_pie.mmap_pie(MatrixCell mmap)
static Matrix	Mmap_sigma.mmap_sigma(Matrix[] mmap)	Computes one-step class transition probabilities for an MMAP given as Matrix[].
static Matrix	Mmap_sigma.mmap_sigma(MatrixCell MMAP)	Computes one-step class transition probabilities for a Marked Markovian Arrival Process (MMAP).
static Matrix[]	Mmpp2_fit_count.mmpp2_fit_count(double mu, double bt1, double bt2, double binf, double m3t2, double t1, double t2)
static Matrix[]	Mmpp2_fit_count_approx.mmpp2_fit_count_approx(double a, double bt1, double bt2, double binf, double m3t2, double t1, double t2)
static Matrix[]	Mmpp2_fitc.mmpp2_fitc(double mu, double bt1, double bt2, double binf, double m3t2, double t1, double t2)	Fits a MMPP(2) according to [Heffes and Lucantoni, 1986].
static Matrix[]	Mmpp2_fitc_approx.mmpp2_fitc_approx(double a, double bt1, double bt2, double binf, double m3t2, double t1, double t2)	Fits a second-order Marked MMPP using optimization.
static Matrix	Qbd_R.qbd_R(Matrix B, Matrix L, Matrix F)
static Matrix	Qbd_R.qbd_R(Matrix B, Matrix L, Matrix F, int iterMax)	Compute R matrix using successive substitutions method for QBD processes.
static Matrix	Qbd_R_logred.qbd_R_logred(Matrix B, Matrix L, Matrix F)
static Matrix	Qbd_R_logred.qbd_R_logred(Matrix B, Matrix L, Matrix F, int iterMax)	Compute R matrix using logarithmic reduction method for QBD processes.
static Matrix	Randp.randp(double[] P, int rows)
static Matrix	Randp.randp(double[] P, int rows, int cols)	Pick random values with relative probability.
static Matrix	Randp.randp(Matrix P, int rows)
static Matrix	Randp.randp(Matrix P, int rows, int cols)

Methods in jline.api.mam that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Aph_bernstein.aph_bernstein(DoubleUnaryOperator f, int order)	Fits an Acyclic Phase-type distribution using Bernstein's approximation.
static Pair<Matrix,Matrix>	Aph_bernstein.aph_bernstein(DoubleUnaryOperator f, int order)	Fits an Acyclic Phase-type distribution using Bernstein's approximation.
static Pair<Matrix,Matrix>	Aph_convseq.aph_convseq(List<Pair<Matrix,Matrix>> aphParams)	Performs sequential convolution of multiple APH distributions.
static Pair<Matrix,Matrix>	Aph_convseq.aph_convseq(List<Pair<Matrix,Matrix>> aphParams)	Performs sequential convolution of multiple APH distributions.
static Pair<Matrix,Matrix>	Aph_simplify.aph_simplify(Matrix a1, Matrix T1, Matrix a2, Matrix T2, double p1, double p2, int pattern)	Simplifies and combines two APH distributions using different structural patterns.
static Pair<Matrix,Matrix>	Aph_simplify.aph_simplify(Matrix a1, Matrix T1, Matrix a2, Matrix T2, double p1, double p2, int pattern)	Simplifies and combines two APH distributions using different structural patterns.
List<Matrix>	LdqbdResult.component1()
List<Matrix>	LdqbdResult.getR()
static Pair<Matrix,Matrix>	Map_pntquad.map_pntquad(Matrix[] MAP, int na, double t)	Compute MAP point process probabilities using ODE quadrature method.
static Pair<Matrix,Matrix>	Map_pntquad.map_pntquad(Matrix[] MAP, int na, double t)	Compute MAP point process probabilities using ODE quadrature method.
static Pair<Matrix,Matrix>	Map2mmpp.map2mmpp(Matrix[] MAP)	Convert a MAP to MMPP format by extracting generator matrix Q and rate matrix LAMBDA.
static Pair<Matrix,Matrix>	Map2mmpp.map2mmpp(Matrix[] MAP)	Convert a MAP to MMPP format by extracting generator matrix Q and rate matrix LAMBDA.
static kotlin.Triple<Matrix,Matrix,MatrixCell>	Map2ph.map2ph(MatrixCell MAP)	Converts a MAP to a Phase-Type (PH) distribution.
static kotlin.Triple<Matrix,Matrix,MatrixCell>	Map2ph.map2ph(MatrixCell MAP)	Converts a MAP to a Phase-Type (PH) distribution.
static kotlin.Pair<MatrixCell,Matrix>	Maph2m_fit.maph2m_fit_multiclass(MatrixCell aph, Matrix P, Matrix B)	Fits MAPH(2,m) for multiple classes given underlying APH(2), class probabilities, and backward moments.

Methods in jline.api.mam with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Aph_simplify.aph_simplify(Matrix a1, Matrix T1, Matrix a2, Matrix T2, double p1, double p2, int pattern)	Simplifies and combines two APH distributions using different structural patterns.
static BmapSample[]	Map_sample.bmap_sample(Matrix D0, Matrix D1_total, Matrix[] Dk, long n, Random random)	Generates samples from a BMAP using D0, D1_total, and individual Dk matrices.
static double	Dmap_dist.dmap_dist(Matrix D0A, Matrix D1A, Matrix D0B, Matrix D1B, int L)	Computes the squared L2 distance between lag-L joint PMFs of two D-MAPs.
static double	Dmap_dist.dmap_dist(Matrix D0A, Matrix D1A, Matrix D0B, Matrix D1B, int L, Matrix alA, Matrix alB)
static double	Dmap_dist.dmap_dist_acf(Matrix D0A, Matrix D1A, Matrix D0B, Matrix D1B)	Computes the squared L2 distance between autocorrelation functions of two D-MAPs.
static double	Dmap_dist.dmap_dist_acf(Matrix D0A, Matrix D1A, Matrix D0B, Matrix D1B, Matrix alA, Matrix alB)
static double	Dmap_dist.dmap_geo_mul_sum(Matrix D0A, Matrix D1A, Matrix D0B, Matrix D1B, int L, Matrix alA, Matrix alB)	Computes the joint PMF inner product of two D-MAPs via recursive discrete Lyapunov equations.
static double	Dmap_dist.dmap_geo_mul_sum_acf(Matrix D0A, Matrix D1A, Matrix D0B, Matrix D1B, Matrix alA, Matrix alB)	Computes the geometric sum for the discrete autocorrelation distance of two D-MAPs.
static double	Dmap_moment.dmap_moment(Matrix D0, Matrix D1, int order)	Computes the k-th raw moment of the inter-arrival time of a discrete MAP.
static Matrix	Dmap_pie.dmap_pie(Matrix D0, Matrix D1)	Computes the stationary vector at arrival epochs of a discrete-time MAP.
static double[]	Dmap_sample.dmap_sample(Matrix D0, Matrix D1, int n, Random random)	Generates samples of inter-arrival times from a discrete-time MAP.
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_bs_multiclass(MatrixCell amap, Matrix P, Matrix B, Matrix S)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_bs_multiclass(MatrixCell amap, Matrix P, Matrix B, Matrix S, Object options, double[] weights)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_fs_multiclass(MatrixCell amap, Matrix P, Matrix F, Matrix S)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_fs_multiclass(MatrixCell amap, Matrix P, Matrix F, Matrix S, Object options, double[] weights)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_gamma_bs(double M1, double M2, double M3, double GAMMA, Matrix P, Matrix B, Matrix S)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_gamma_bs_trace(Matrix T, Matrix A)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_gamma_fs(double M1, double M2, double M3, double GAMMA, Matrix P, Matrix F, Matrix S)
static MatrixCell	Mamap22_fit_multiclass.mamap22_fit_gamma_fs_trace(Matrix T, Matrix A)
static Matrix[]	Mamap2m_fit.mamap2m_fit(double M1, double M2, double M3, double GAMMA, double[] P, double[] F, double[] B, Matrix S)
static Matrix[]	Mamap2m_fit.mamap2m_fit(double M1, double M2, double M3, double GAMMA, double[] P, double[] F, double[] B, Matrix S, double[] fbsWeights)
static MatrixCell	Mamap2m_fit_gamma_fb_trace.mamap2m_fit_gamma_fb_trace(Matrix T, Matrix A)	Performs approximate fitting of a marked trace from Matrix inputs.
static Matrix	Map_acf.map_acf(MatrixCell MAP, Matrix lags)
static Matrix	Map_acf.map_acf(Matrix D0, Matrix D1)
static Matrix	Map_acf.map_acf(Matrix D0, Matrix D1, int lag)
static Matrix	Map_acf.map_acf(Matrix D0, Matrix D1, Matrix lags)	Computes the autocorrelation function (ACF) for a given MAP at multiple lags.
static double[]	Map_acfc.map_acfc(Matrix D0, Matrix D1, int[] lags, double u)	Computes the autocorrelation function coefficients (ACFC) for a MAP counting process.
static double	Map_ccdf_derivative.map_ccdf_derivative(Matrix D0, Matrix D1, int i)	Compute derivative at 0 of a MAP complementary CDF.
static Matrix	Map_cdf.map_cdf(MatrixCell MAP, Matrix points)	CDF of MAP inter-arrival times when MAP is a MatrixCell.
static Matrix	Map_cdf.map_cdf(Matrix D0, Matrix D1, Matrix points)	Computes the cumulative distribution function (CDF) of the inter-arrival times of a Markovian Arrival Process (MAP).
static boolean	Map_checkfeasible.map_checkfeasible(Matrix D0, Matrix D1)
static boolean	Map_checkfeasible.map_checkfeasible(Matrix D0, Matrix D1, double TOL)	Check the feasibility of a MAP given separate D0 and D1 matrices.
static double	Map_dist.map_dist(Matrix A0, Matrix A1, Matrix B0, Matrix B1, int L)	Computes the squared L2 distance between lag-L joint densities of two MAPs.
static double	Map_dist.map_dist(Matrix A0, Matrix A1, Matrix B0, Matrix B1, int L, Matrix alA, Matrix alB)	Computes the squared L2 distance between lag-L joint densities of two MAPs.
static double	Map_dist_acf.map_dist_acf(Matrix A0, Matrix A1, Matrix B0, Matrix B1)	Computes the squared L2 distance between autocorrelation functions of two MAPs.
static double	Map_dist_acf.map_dist_acf(Matrix A0, Matrix A1, Matrix B0, Matrix B1, Matrix alA, Matrix alB)	Computes the squared L2 distance between autocorrelation functions of two MAPs.
static Matrix	Map_embedded.map_embedded(Matrix D0, Matrix D1)	Computes the embedded discrete-time Markov chain (DTMC) matrix of a MAP.
static double	Map_exp_mul_int.map_exp_mul_int(Matrix A0, Matrix A1, Matrix B0, Matrix B1, int L, Matrix alA, Matrix alB)	Computes the inner product of lag-L joint densities of two MAPs.
static double	Map_gamma.map_gamma(Matrix D0, Matrix D1)	Computes the gamma parameter for a MAP, which is the autocorrelation decay rate.
static double	Map_dist_acf.map_geo_mul_sum(Matrix A0, Matrix A1, Matrix B0, Matrix B1, Matrix alA, Matrix alB)	Computes the geometric sum needed for the autocorrelation distance.
static double	Map_idc.map_idc(Matrix D0, Matrix D1)	Computes the asymptotic index of dispersion (IDC) for a Markovian Arrival Process (MAP).
static Matrix	Map_infgen.map_infgen(Matrix D0, Matrix D1)	Computes the infinitesimal generator matrix (Q) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static double	Map_joint.map_joint(Matrix D0, Matrix D1, int[] a, int[] i)	Computes the joint moments of a Markovian Arrival Process (MAP).
static double	Map_jointpdf_derivative.map_jointpdf_derivative(Matrix D0, Matrix D1, int[] iset)	Compute partial derivative at 0 of a MAP's joint PDF.
static Matrix[]	Map_kpc.map_kpc(Matrix[] MAPa, Matrix[] MAPb)	Convenience function for composing exactly two MAPs.
static double	Map_lambda.map_lambda(Matrix D0, Matrix D1)	Computes the arrival rate (lambda) of a Markovian Arrival Process (MAP).
static MatrixCell	Map_mark.map_mark(MatrixCell MAP, Matrix prob)	Creates a Marked Markovian Arrival Process (MMAP) by marking a given MAP with additional phases based on specified marking probabilities.
static double	Map_mean.map_mean(Matrix D0, Matrix D1)	Computes the mean inter-arrival time of a Markovian Arrival Process (MAP).
static double	Map_moment.map_moment(Matrix D0, Matrix D1, int order)	Computes the raw moments of the inter-arrival times of a MAP.
static MatrixCell	Map_normalize.map_normalize(Matrix D0, Matrix D1)	Sanitizes the (D0, D1) matrices of a Markovian Arrival Process (MAP).
static double	Map_pdf.map_pdf(Matrix D0, Matrix D1, double t)
static double[]	Map_pdf.map_pdf(Matrix D0, Matrix D1, double[] tset)
static Matrix	Map_pie.map_pie(Matrix D0, Matrix D1)	Computes the steady-state probability vector of the embedded Discrete Time Markov Chain (DTMC) associated with a Markovian Arrival Process (MAP).
static Matrix	Map_piq.map_piq(Matrix D0, Matrix D1)	Computes the steady-state vector (pi) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static Matrix	Map_pntiter.map_pntiter(Matrix[] MAP, int na, double t)
static Matrix	Map_pntiter.map_pntiter(Matrix[] MAP, int na, double t, Integer M)	Probability of having exactly na arrivals within time interval t using iterative method.
static Pair<Matrix,Matrix>	Map_pntquad.map_pntquad(Matrix[] MAP, int na, double t)	Compute MAP point process probabilities using ODE quadrature method.
static Matrix	Map_prob.map_prob(Matrix D0, Matrix D1)	Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
static MatrixCell	Map_renewal.map_renewal(Matrix D0, Matrix D1)	Creates a renewal MAP by removing all correlations from the input MAP.
static double[]	Map_sample.map_sample(Matrix D0, Matrix D1, long n, Random random)	Generates samples of inter-arrival times from a MAP using a specified number of samples and a random generator.
static MatrixCell	Map_scale.map_scale(Matrix D0, Matrix D1, double newMean)	Rescales the mean inter-arrival time of a Markovian Arrival Process (MAP) to a specified new mean.
static double	Map_scv.map_scv(Matrix D0, Matrix D1)	Computes the squared coefficient of variation (SCV) of the inter-arrival times of a Markovian Arrival Process (MAP).
static double	Map_skew.map_skew(Matrix D0, Matrix D1)	Computes the skewness of the inter-arrival times for a MAP.
static MatrixCell	Map_stochcomp.map_stochcomp(Matrix D0, Matrix D1, int[] retainIdx)	Performs stochastic complementation on a MAP by eliminating specified states.
static double	Map_var.map_var(Matrix D0, Matrix D1)	Computes the variance of the inter-arrival times for a MAP.
static Matrix	Map_varcount.map_varcount(MatrixCell MAP, Matrix t)
static double	Map_varcount.map_varcount(Matrix D0, Matrix D1, double t)	Variance of the counts in a MAP over a time period t.
static Matrix	Map_varcount.map_varcount(Matrix D0, Matrix D1, Matrix t)	Variance of the counts in a MAP over multiple time periods.
static Pair<Matrix,Matrix>	Map2mmpp.map2mmpp(Matrix[] MAP)	Convert a MAP to MMPP format by extracting generator matrix Q and rate matrix LAMBDA.
static MatrixCell	Maph2m_fit.maph2m_fit(double M1, double M2, double M3, Matrix P, Matrix B)	Computes the second-order MAPH[m] fitting given moments, class probs, and backward moments.
static kotlin.Pair<MatrixCell,Matrix>	Maph2m_fit.maph2m_fit_multiclass(MatrixCell aph, Matrix P, Matrix B)	Fits MAPH(2,m) for multiple classes given underlying APH(2), class probabilities, and backward moments.
static double	Me_mean.me_mean(Matrix alpha, Matrix A)	Computes the mean of a Matrix Exponential (ME) distribution.
static Matrix	Me_pie.me_pie(Matrix H0, Matrix H1)	Computes the stationary initial probability for an ME/RAP distribution.
static double[]	Me_sample.me_sample(Matrix alpha, Matrix A, long n, Random random)	Generates random samples from a Matrix Exponential (ME) distribution using inverse CDF interpolation.
static double	Me_scv.me_scv(Matrix alpha, Matrix A)	Computes the squared coefficient of variation (SCV) of a Matrix Exponential (ME) distribution.
static double	Me_var.me_var(Matrix alpha, Matrix A)	Computes the variance of a Matrix Exponential (ME) distribution.
static Matrix	Mmap_backward_moment.mmap_backward_moment(MatrixCell MMAP, Matrix ORDERS)
static Matrix	Mmap_backward_moment.mmap_backward_moment(MatrixCell MMAP, Matrix ORDERS, int NORM)	Computes the backward moments of an MMAP for specified orders with normalization.
static Matrix[]	Mmap_compress.mmap_compress(Matrix[] mmap)
static Matrix[]	Mmap_compress.mmap_compress(Matrix[] mmap, String method)
static Matrix	Mmap_count_mcov.mmap_count_mcov(Matrix[] mmap, double t)	Array-based overload.
static MatrixCell	Mmap_exponential.mmap_exponential(Matrix lambda)	Fits a single-state MMAP based on the given arrival rates for each job class.
static MatrixCell	Mmap_exponential.mmap_exponential(Matrix lambda, int n)	Fits an order-n MMAP based on the given arrival rates for each job class.
static Matrix	Mmap_forward_moment.mmap_forward_moment(MatrixCell MMAP, Matrix ORDERS)
static Matrix	Mmap_forward_moment.mmap_forward_moment(MatrixCell MMAP, Matrix ORDERS, int NORM)	Computes the forward moments of an MMAP for specified orders with normalization.
static MatrixCell	Mmap_hide.mmap_hide(MatrixCell MMAP, Matrix types)	Hides specified types of arrivals in a Markovian Arrival Process with marked arrivals (MMAP).
static MatrixCell	Mmap_mark.mmap_mark(MatrixCell MMAP, Matrix prob)	Converts a Markovian Arrival Process with marked arrivals (MMAP) into a new MMAP with redefined classes based on a given probability matrix.
static MatrixCell	Mmap_mixture.mmap_mixture(Matrix alpha, Map<Integer,MatrixCell> MAPs)	Creates a mixture of MMAPs using the given weights (alpha) and MAPs.
static Ret.mamMMAPMixtureFit	Mmap_mixture_fit.mmap_mixture_fit(Object P2, Matrix M1, Matrix M2, Matrix M3)	Fits a mixture of Markovian Arrival Processes (MMAPs) to match the given cross-moments.
static Ret.mamMMAPMixtureFit	Mmap_mixture_fit_trace.mmap_mixture_fit_trace(Matrix T, Matrix A)	Fits a MMAP with m classes using a mixture of m^2 PH-distributions from Matrix inputs.
static Matrix	Mmap_pie.mmap_pie(Matrix[] mmap)
static MatrixCell	Mmap_scale.mmap_scale(MatrixCell MMAP, Matrix M)	Overloaded function for backward compatibility.
static MatrixCell	Mmap_scale.mmap_scale(MatrixCell MMAP, Matrix M, int maxIter)	Changes the mean inter-arrival time of a Markovian Arrival Process with marked arrivals (MMAP).
static Matrix	Mmap_sigma.mmap_sigma(Matrix[] mmap)	Computes one-step class transition probabilities for an MMAP given as Matrix[].
static Qbd_bmapbmap1.QbdBmapResult	Qbd_bmapbmap1.qbd_bmapbmap1(MatrixCell MAPa, Matrix pbatcha, MatrixCell MAPs)	Set up QBD matrices for BMAP/BMAP/1 queue analysis.
static double[]	Qbd_depproc_jointmom.qbd_depproc_jointmom(MatrixCell MAPa, MatrixCell MAPs, Matrix iset)	Compute joint moments of consecutive inter-departure times.
static Matrix	Qbd_R.qbd_R(Matrix B, Matrix L, Matrix F)
static Matrix	Qbd_R.qbd_R(Matrix B, Matrix L, Matrix F, int iterMax)	Compute R matrix using successive substitutions method for QBD processes.
static Matrix	Qbd_R_logred.qbd_R_logred(Matrix B, Matrix L, Matrix F)
static Matrix	Qbd_R_logred.qbd_R_logred(Matrix B, Matrix L, Matrix F, int iterMax)	Compute R matrix using logarithmic reduction method for QBD processes.
static int	Randp.randp(Matrix P)
static Matrix	Randp.randp(Matrix P, int rows)
static Matrix	Randp.randp(Matrix P, int rows, int cols)

Method parameters in jline.api.mam with type arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Aph_convseq.aph_convseq(List<Pair<Matrix,Matrix>> aphParams)	Performs sequential convolution of multiple APH distributions.
static Pair<Matrix,Matrix>	Aph_convseq.aph_convseq(List<Pair<Matrix,Matrix>> aphParams)	Performs sequential convolution of multiple APH distributions.
static LdqbdResult	Ldqbd.ldqbd(List<Matrix> Q0, List<Matrix> Q1, List<Matrix> Q2)
static LdqbdResult	Ldqbd.ldqbd(List<Matrix> Q0, List<Matrix> Q1, List<Matrix> Q2, LdqbdOptions options)

Constructors in jline.api.mam with parameters of type Matrix

Modifier	Constructor	Description
	LdqbdResult(List<Matrix> R, Matrix pi)
	Mamap2mCoefficients(Matrix first, Matrix second, Matrix third)
	QbdBmapResult(Matrix A0, Matrix A_1, List<Matrix> A1, Matrix B0, List<Matrix> B1)
	QbdCrResult(Matrix G, Matrix R, Matrix U)
	QbdMapMap1Result(double XN, double QN, double UN, Matrix pqueue, Matrix R, Matrix eta, Matrix G, Matrix A_1, Matrix A0, Matrix A1, Matrix U, MatrixCell MAPs)
	QbdRapRap1Result(double XN, double QN, double UN, Matrix pqueue, Matrix R, Matrix eta, Matrix G, Matrix B, Matrix L, Matrix F)
	QbdRgResult(Matrix R, Matrix G, Matrix B, Matrix L, Matrix F, Matrix U)

Constructor parameters in jline.api.mam with type arguments of type Matrix

Modifier	Constructor	Description
	LdqbdResult(List<Matrix> R, Matrix pi)
	QbdBmapResult(Matrix A0, Matrix A_1, List<Matrix> A1, Matrix B0, List<Matrix> B1)

Uses of Matrix in jline.api.mam.m3pp

Methods in jline.api.mam.m3pp that return Matrix

Modifier and Type	Method	Description
static Matrix[]	M3pp22_fitc_approx_cov.m3pp22_fitc_approx_cov(double a, double bt1, double bt2, double binf, double m3t2, double t1, double t2, double[] ai, double st3, double t3)	Fits a second-order Marked MMPP for two classes using covariance approximation.
static Matrix[]	M3pp22_fitc_approx_cov_multiclass.m3pp22_fitc_approx_cov_multiclass(Matrix[] mmpp, double[] ai, double st3, double t3)	Fits a M3PP(2,2) given the underlying MMPP(2).
static Matrix[]	M3pp2m_fitc.m3pp2m_fitc(double a, double bt1, double bt2, double binf, double m3t2, double t1, double t2, double[] ai, double[] dvt3, double t3)	Fits a second-order Marked MMPP using exact count statistics.
static Matrix[]	M3pp2m_fitc_approx.m3pp2m_fitc_approx(double a, double bt1, double bt2, double binf, double m3t2, double t1, double t2, double[] ai, double[] dvt3, double t3)
static Matrix[]	M3pp2m_fitc_approx_ag.m3pp2m_fitc_approx_ag(double a, double bt1, double bt2, double binf, double m3t2, double t1, double t2, double[] ai, double[] gt3, double t3)	Fits a second-order Marked MMPP using auto-gamma approach.
static Matrix[]	M3pp2m_fitc_approx_ag_multiclass.m3pp2m_fitc_approx_ag_multiclass(Matrix[] mmpp, double[] ai, double[] gt3, double t3)
static Matrix[]	M3pp2m_fitc_theoretical.m3pp2m_fitc_theoretical(MatrixCell mmap)
static Matrix[]	M3pp2m_fitc_theoretical.m3pp2m_fitc_theoretical(MatrixCell mmap, String method)
static Matrix[]	M3pp2m_fitc_theoretical.m3pp2m_fitc_theoretical(MatrixCell mmap, String method, double t)
static Matrix[]	M3pp2m_fitc_theoretical.m3pp2m_fitc_theoretical(MatrixCell mmap, String method, double t, double tinf)	Fits the theoretical characteristics of a MMAP(n,m) with a M3PP(2,m).
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(double[] T, int[] A)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(double[] T, int[] A, String method)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(double[] T, int[] A, String method, Double t1, Double tinf)	Fits a M3PP(2,m) from trace data using counting process characteristics.
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(Matrix T, Matrix A)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(Matrix T, Matrix A, String method)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(Matrix T, Matrix A, String method, Double t1, Double tinf)	Fits a M3PP(2,m) from trace data using Matrix inputs.

Methods in jline.api.mam.m3pp with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix[],List<Matrix[]>>	M3pp_superpos_fitc_trace.m3pp_superpos_fitc_trace(Matrix T, Matrix A)
static Pair<Matrix[],List<Matrix[]>>	M3pp_superpos_fitc_trace.m3pp_superpos_fitc_trace(Matrix T, Matrix A, Double t, Double tinf)	Superposes k M3PP processes to fit a multi-class trace from Matrix inputs.
static Matrix[]	M3pp22_fitc_approx_cov_multiclass.m3pp22_fitc_approx_cov_multiclass(Matrix[] mmpp, double[] ai, double st3, double t3)	Fits a M3PP(2,2) given the underlying MMPP(2).
static Matrix[]	M3pp2m_fitc_approx_ag_multiclass.m3pp2m_fitc_approx_ag_multiclass(Matrix[] mmpp, double[] ai, double[] gt3, double t3)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(Matrix T, Matrix A)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(Matrix T, Matrix A, String method)
static Matrix[]	M3pp2m_fitc_trace.m3pp2m_fitc_trace(Matrix T, Matrix A, String method, Double t1, Double tinf)	Fits a M3PP(2,m) from trace data using Matrix inputs.

Uses of Matrix in jline.api.map

Methods in jline.api.map with parameters of type Matrix

Modifier and Type	Method	Description
static double[]	MAPM1PSCdfRespT.computeCdf(Matrix C, Matrix D, double mu, double[] x)
static double[]	MAPM1PSCdfRespT.computeCdf(Matrix C, Matrix D, double mu, double[] x, double epsilon)
static double[]	MAPM1PSCdfRespT.computeCdf(Matrix C, Matrix D, double mu, double[] x, double epsilon, double epsilonPrime)

Uses of Matrix in jline.api.mapqn

Fields in jline.api.mapqn declared as Matrix

Modifier and Type	Field	Description
final Matrix	Mapqn_qr_bounds_bas_parameters.BB
final Matrix	Mapqn_qr_bounds_bas_parameters.MM
final Matrix	Mapqn_qr_bounds_bas_parameters.MM1
final Matrix[]	LinearReductionParameters.mu
final Matrix[]	Mapqn_qr_bounds_bas_parameters.mu
final Matrix[]	Mapqn_qr_bounds_rsrd_parameters.mu
final Matrix	MVAVersionParameters.muMAP
final Matrix	LinearReductionParameters.r
final Matrix	Mapqn_qr_bounds_bas_parameters.r
final Matrix	Mapqn_qr_bounds_rsrd_parameters.r
final Matrix	MVAVersionParameters.r
final Matrix[]	LinearReductionParameters.v
final Matrix[]	Mapqn_qr_bounds_bas_parameters.v
final Matrix[]	Mapqn_qr_bounds_rsrd_parameters.v
final Matrix	MVAVersionParameters.v

Methods in jline.api.mapqn that return Matrix

Modifier and Type	Method	Description
Matrix[][]	Mapqn_qr_bounds_bas_parameters.q()

Constructors in jline.api.mapqn with parameters of type Matrix

Modifier	Constructor	Description
	LinearReductionParameters(int M, int N, int[] K, Matrix[] mu, Matrix r, Matrix[] v)
	Mapqn_qr_bounds_bas_parameters(int M, int N, int MR, int f, int[] K, int[] F, Matrix MM, Matrix MM1, int[] ZZ, Matrix BB, Matrix[] mu, Matrix[] v, Matrix r)
	Mapqn_qr_bounds_rsrd_parameters(int M, int N, int[] F, int[] K, Matrix[] mu, Matrix[] v, double[][] alpha, Matrix r)
	MVAVersionParameters(int M, int N, int K, double[] muM, Matrix muMAP, Matrix r, Matrix v)

Uses of Matrix in jline.api.mc

Fields in jline.api.mc declared as Matrix

Modifier and Type	Field	Description
final Matrix	Ctmc_multi.CtmcMultiResult.p
final Matrix	Ctmc_solve_reducible.CtmcSolveReducibleResult.pi
final Matrix	Dtmc_solve_reducible.DtmcSolveReducibleResult.pi
final Matrix	Dtmc_uniformization.DtmcUniformizationResult.pi
final Matrix	Ctmc_solve_reducible.CtmcSolveReducibleResult.pi0
final Matrix	Dtmc_solve_reducible.DtmcSolveReducibleResult.pi0
final Matrix	Dtmc_solve_reducible.DtmcSolveReducibleResult.pil
final Matrix	Dtmc_solve_reducible.DtmcSolveReducibleResult.Pl
final Matrix	CtmcSsgReachabilityResult.stateSpace
final Matrix	CtmcSsgReachabilityResult.stateSpaceAggr
final Matrix	CtmcSsgReachabilityResult.stateSpaceHashed

Fields in jline.api.mc with type parameters of type Matrix

Modifier and Type	Field	Description
final Map<StatefulNode,Matrix>	CtmcSsgReachabilityResult.nodeStateSpace
final List<Matrix>	Ctmc_solve_reducible.CtmcSolveReducibleResult.pis
final List<Matrix>	Dtmc_solve_reducible.DtmcSolveReducibleResult.pis

Methods in jline.api.mc that return Matrix

Modifier and Type	Method	Description
Matrix	Dtmc_uniformization.DtmcUniformizationResult.component1()
static Matrix	Ctmc_makeinfgen.ctmc_makeinfgen(Matrix Q)	Converts a matrix into a valid infinitesimal generator for a CTMC.
static Matrix	Ctmc_rand.ctmc_rand(int length)	Form a random infinitesimal generator of a CTMC
static Matrix	Ctmc_solve.ctmc_solve(Matrix Q)	Return the steady-state probability of a CTMC.
static Matrix	Ctmc_stmonotone.ctmc_stmonotone(Matrix Q)	Computes the stochastically monotone upper bound for a CTMC.
static Matrix	Ctmc_timereverse.ctmc_timereverse(Matrix Q)	Compute the infinitesimal generator of the time-reserved CTMC
static Matrix	Ctmc_uniformization.ctmc_uniformization(Matrix pi0, Matrix Q, double t)	Return the transient probability distribution of the CTMC via the uniformization method.
static Matrix	Dtmc_makestochastic.dtmc_makestochastic(Matrix P)	Normalize a given non-negative matrix into a DTMC.
static Matrix	Dtmc_rand.dtmc_rand(int length)	Form a random infinitesimal generator of a DTMC
static Matrix	Dtmc_solve.dtmc_solve(Matrix P)	Returns the steady-state solution of a DTMC.
static Matrix	Ctmc_stmonotone.dtmc_stmonotone(Matrix P)	Implementation of the dtmc_stmonotone algorithm.
static Matrix	Dtmc_stochcomp.dtmc_stochcomp(Matrix P, List<Integer> I)	Returns the stochastic complement of a DTMC.
static Matrix	Dtmc_timereverse.dtmc_timereverse(Matrix P)	Compute the infinitesimal generator of the time-reversed DTMC.
Matrix	Ctmc_solve_reducible_blkdecompResult.getPi()
Matrix	Ctmc_solve_reducible_blkdecompResult.getPi0()
Matrix	CtmcSsgReachabilityResult.getStateSpace()
Matrix	CtmcSsgReachabilityResult.getStateSpaceAggr()
Matrix	CtmcSsgReachabilityResult.getStateSpaceHashed()

Methods in jline.api.mc that return types with arguments of type Matrix

Modifier and Type	Method	Description
static kotlin.Triple<Matrix,Double,Double>	Ctmc_courtois.ctmc_courtois(Matrix Q, List<List<Integer>> MS)
static kotlin.Triple<Matrix,Double,Double>	Ctmc_courtois.ctmc_courtois(Matrix Q, List<List<Integer>> MS, double q)	Courtois decomposition for nearly completely decomposable CTMCs
static kotlin.Triple<Matrix,Double,Double>	Ctmc_kms.ctmc_kms(Matrix Q, List<List<Integer>> MS, int numSteps)	Koury-McAllister-Stewart aggregation-disaggregation method for CTMCs
static Pair<Matrix,Double>	Ctmc_randomization.ctmc_randomization(Matrix Q)
static Pair<Matrix,Double>	Ctmc_randomization.ctmc_randomization(Matrix Q, Double q)	Convert a CTMC to a DTMC using randomization technique
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible.ctmc_solve_reducible(Matrix Q)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible.ctmc_solve_reducible(Matrix Q, Matrix pi0)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible.ctmc_solve_reducible(Matrix Q, Matrix pi0, Map<String,Object> options)	Solve reducible CTMCs by converting to DTMC via randomization.
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp(Matrix Q)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp(Matrix Q, Matrix pi0)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp(Matrix Q, Matrix pi0, Map<String,Object> options)
static kotlin.Triple<Matrix,Double,Double>	Ctmc_takahashi.ctmc_takahashi(Matrix Q, List<List<Integer>> MS, int numSteps)	Takahashi's aggregation-disaggregation method for CTMCs
static Pair<Matrix,List<List<Integer>>>	Dtmc_solve_reducible.dtmc_solve_reducible(Matrix P)
static Pair<Matrix,List<List<Integer>>>	Dtmc_solve_reducible.dtmc_solve_reducible(Matrix P, Matrix pin)
static Pair<Matrix,List<List<Integer>>>	Dtmc_solve_reducible.dtmc_solve_reducible(Matrix P, Matrix pin, Map<String,Object> options)	Estimate limiting distribution for a DTMC that may have reducible components.
Map<StatefulNode,Matrix>	CtmcSsgReachabilityResult.getNodeStateSpace()
List<Matrix>	Ctmc_solve_reducible_blkdecompResult.getPis()

Methods in jline.api.mc with parameters of type Matrix

Modifier and Type	Method	Description
static kotlin.Triple<Matrix,Double,Double>	Ctmc_courtois.ctmc_courtois(Matrix Q, List<List<Integer>> MS)
static kotlin.Triple<Matrix,Double,Double>	Ctmc_courtois.ctmc_courtois(Matrix Q, List<List<Integer>> MS, double q)	Courtois decomposition for nearly completely decomposable CTMCs
static kotlin.Triple<Matrix,Double,Double>	Ctmc_kms.ctmc_kms(Matrix Q, List<List<Integer>> MS, int numSteps)	Koury-McAllister-Stewart aggregation-disaggregation method for CTMCs
static Matrix	Ctmc_makeinfgen.ctmc_makeinfgen(Matrix Q)	Converts a matrix into a valid infinitesimal generator for a CTMC.
static Ctmc_multi.CtmcMultiResult	Ctmc_multi.ctmc_multi(Matrix Q, List<List<Integer>> MS, List<List<Integer>> MSS)	Multi-level aggregation method for CTMCs.
static SolverCTMC.StochCompResult	Ctmc_pseudostochcomp.ctmc_pseudostochcomp(Matrix Q, List<Double> I_list)
static Pair<Matrix,Double>	Ctmc_randomization.ctmc_randomization(Matrix Q)
static Pair<Matrix,Double>	Ctmc_randomization.ctmc_randomization(Matrix Q, Double q)	Convert a CTMC to a DTMC using randomization technique
static Object[]	Ctmc_relsolve.ctmc_relsolve(Matrix Q)
static Object[]	Ctmc_relsolve.ctmc_relsolve(Matrix Q, int refstate)
static Object[]	Ctmc_relsolve.ctmc_relsolve(Matrix Q, int refstate, Map<String,Object> options)	Equilibrium distribution of a continuous-time Markov chain re-normalized with respect to the probability of a reference state.
static Ret.ctmcSimulation	Ctmc_simulate.ctmc_simulate(Matrix Q, double[] pi0, int n)
static Ret.ctmcSimulation	Ctmc_simulate.ctmc_simulate(Matrix Q, double[] pi0, int n, Random random)
static Matrix	Ctmc_solve.ctmc_solve(Matrix Q)	Return the steady-state probability of a CTMC.
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible.ctmc_solve_reducible(Matrix Q)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible.ctmc_solve_reducible(Matrix Q, Matrix pi0)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible.ctmc_solve_reducible(Matrix Q, Matrix pi0, Map<String,Object> options)	Solve reducible CTMCs by converting to DTMC via randomization.
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp(Matrix Q)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp(Matrix Q, Matrix pi0)
static Pair<Matrix,List<List<Integer>>>	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp(Matrix Q, Matrix pi0, Map<String,Object> options)
static Ctmc_solve_reducible_blkdecompResult	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp_full(Matrix Q)
static Ctmc_solve_reducible_blkdecompResult	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp_full(Matrix Q, Matrix pi0)
static Ctmc_solve_reducible_blkdecompResult	Ctmc_solve_reducible_blkdecomp.ctmc_solve_reducible_blkdecomp_full(Matrix Q, Matrix pi0, Map<String,Object> options)
static Ctmc_solve_reducible.CtmcSolveReducibleResult	Ctmc_solve_reducible.ctmc_solve_reducible_full(Matrix Q)
static Ctmc_solve_reducible.CtmcSolveReducibleResult	Ctmc_solve_reducible.ctmc_solve_reducible_full(Matrix Q, Matrix pi0)
static Ctmc_solve_reducible.CtmcSolveReducibleResult	Ctmc_solve_reducible.ctmc_solve_reducible_full(Matrix Q, Matrix pi0, Map<String,Object> options)	Alternative signature that returns additional information.
static Matrix	Ctmc_stmonotone.ctmc_stmonotone(Matrix Q)	Computes the stochastically monotone upper bound for a CTMC.
static SolverCTMC.StochCompResult	Ctmc_stochcomp.ctmc_stochcomp(Matrix Q, List<Double> I_list)
static kotlin.Triple<Matrix,Double,Double>	Ctmc_takahashi.ctmc_takahashi(Matrix Q, List<List<Integer>> MS, int numSteps)	Takahashi's aggregation-disaggregation method for CTMCs
static boolean	Ctmc_testpf_kolmogorov.ctmc_testpf_kolmogorov(Matrix Q)	Test if a CTMC has product form using Kolmogorov's criteria.
static Matrix	Ctmc_timereverse.ctmc_timereverse(Matrix Q)	Compute the infinitesimal generator of the time-reserved CTMC
static Pair<double[],List<double[]>>	Ctmc_transient.ctmc_transient(Matrix Q, double t1)
static Pair<double[],List<double[]>>	Ctmc_transient.ctmc_transient(Matrix Q, Matrix pi0, double t1)
static Pair<double[],List<double[]>>	Ctmc_transient.ctmc_transient(Matrix Q, Matrix pi0, double t0, double t1)
static Pair<double[],List<double[]>>	Ctmc_transient.ctmc_transient(Matrix Q, Matrix pi0, double t0, double t1, Double timestep)
static Matrix	Ctmc_uniformization.ctmc_uniformization(Matrix pi0, Matrix Q, double t)	Return the transient probability distribution of the CTMC via the uniformization method.
static int	Dtmc_isfeasible.dtmc_isfeasible(Matrix P)	Check if a matrix represents a feasible DTMC transition matrix
static Matrix	Dtmc_makestochastic.dtmc_makestochastic(Matrix P)	Normalize a given non-negative matrix into a DTMC.
static int[]	Dtmc_simulate.dtmc_simulate(Matrix P, Matrix pi0, int n)	Simulate a discrete-time Markov chain trajectory.
static Matrix	Dtmc_solve.dtmc_solve(Matrix P)	Returns the steady-state solution of a DTMC.
static Pair<Matrix,List<List<Integer>>>	Dtmc_solve_reducible.dtmc_solve_reducible(Matrix P)
static Pair<Matrix,List<List<Integer>>>	Dtmc_solve_reducible.dtmc_solve_reducible(Matrix P, Matrix pin)
static Pair<Matrix,List<List<Integer>>>	Dtmc_solve_reducible.dtmc_solve_reducible(Matrix P, Matrix pin, Map<String,Object> options)	Estimate limiting distribution for a DTMC that may have reducible components.
static Dtmc_solve_reducible.DtmcSolveReducibleResult	Dtmc_solve_reducible.dtmc_solve_reducible_full(Matrix P)
static Dtmc_solve_reducible.DtmcSolveReducibleResult	Dtmc_solve_reducible.dtmc_solve_reducible_full(Matrix P, Matrix pin)
static Dtmc_solve_reducible.DtmcSolveReducibleResult	Dtmc_solve_reducible.dtmc_solve_reducible_full(Matrix P, Matrix pin, Map<String,Object> options)	Full version that returns all computed values.
static Matrix	Ctmc_stmonotone.dtmc_stmonotone(Matrix P)	Implementation of the dtmc_stmonotone algorithm.
static Matrix	Dtmc_stochcomp.dtmc_stochcomp(Matrix P, List<Integer> I)	Returns the stochastic complement of a DTMC.
static Matrix	Dtmc_timereverse.dtmc_timereverse(Matrix P)	Compute the infinitesimal generator of the time-reversed DTMC.
static Dtmc_uniformization.DtmcUniformizationResult	Dtmc_uniformization.dtmc_uniformization(Matrix pi0, Matrix P)
static Dtmc_uniformization.DtmcUniformizationResult	Dtmc_uniformization.dtmc_uniformization(Matrix pi0, Matrix P, double t)
static Dtmc_uniformization.DtmcUniformizationResult	Dtmc_uniformization.dtmc_uniformization(Matrix pi0, Matrix P, double t, double tol)
static Dtmc_uniformization.DtmcUniformizationResult	Dtmc_uniformization.dtmc_uniformization(Matrix pi0, Matrix P, double t, double tol, int maxiter)	Compute the transient probability distribution of a DTMC using uniformization.

Constructors in jline.api.mc with parameters of type Matrix

Modifier	Constructor	Description
	Ctmc_solve_reducible_blkdecompResult(Matrix pi, List<Matrix> pis, Matrix pi0, List<List<Integer>> scc, List<Boolean> isrec)
	CtmcMultiResult(Matrix p, double eps, double epsMAX)
	CtmcSolveReducibleResult(Matrix pi, List<Matrix> pis, Matrix pi0, List<List<Integer>> scc, List<Boolean> isrec)
	CtmcSsgReachabilityResult(Matrix stateSpace, Matrix stateSpaceAggr, Matrix stateSpaceHashed, Map<StatefulNode,Matrix> nodeStateSpace, NetworkStruct sn)
	DtmcSolveReducibleResult(Matrix pi, List<Matrix> pis, Matrix pi0, List<List<Integer>> scc, List<Boolean> isrec, Matrix Pl, Matrix pil)
	DtmcUniformizationResult(Matrix pi, int kmax)

Constructor parameters in jline.api.mc with type arguments of type Matrix

Modifier	Constructor	Description
	Ctmc_solve_reducible_blkdecompResult(Matrix pi, List<Matrix> pis, Matrix pi0, List<List<Integer>> scc, List<Boolean> isrec)
	CtmcSolveReducibleResult(Matrix pi, List<Matrix> pis, Matrix pi0, List<List<Integer>> scc, List<Boolean> isrec)
	CtmcSsgReachabilityResult(Matrix stateSpace, Matrix stateSpaceAggr, Matrix stateSpaceHashed, Map<StatefulNode,Matrix> nodeStateSpace, NetworkStruct sn)
	DtmcSolveReducibleResult(Matrix pi, List<Matrix> pis, Matrix pi0, List<List<Integer>> scc, List<Boolean> isrec, Matrix Pl, Matrix pil)

Uses of Matrix in jline.api.measures

Methods in jline.api.measures with parameters of type Matrix

Modifier and Type	Method	Description
static double	Ms_additivesymmetricchisquared.ms_additivesymmetricchisquared(Matrix P, Matrix Q)	Additive symmetric chi-squared distance between two probability distributions.
static double	Ms_anderson_darling.ms_anderson_darling(Matrix XX, Matrix YY)	Anderson-Darling distance between two empirical distributions.
static double	Ms_avgl1linfty.ms_avgl1linfty(Matrix P, Matrix Q)	Average L1 L-infinity distance between two probability distributions.
static double	Ms_bhattacharyya.ms_bhattacharyya(Matrix P, Matrix Q)	Bhattacharyya distance between two probability distributions.
static double	Ms_canberra.ms_canberra(Matrix P, Matrix Q)	Canberra distance between two probability distributions.
static double	Ms_chebyshev.ms_chebyshev(Matrix P, Matrix Q)	Chebyshev distance between two probability distributions.
static double	Ms_cityblock.ms_cityblock(Matrix P, Matrix Q)	City block (Manhattan) distance between two probability distributions.
static double	Ms_clark.ms_clark(Matrix P, Matrix Q)	Clark distance between two probability distributions.
static double	Ms_condentropy.ms_condentropy(Matrix x, Matrix y)	Compute conditional entropy z=H(x|y) of two discrete variables x and y.
static double	Ms_cosine.ms_cosine(Matrix P, Matrix Q)	Cosine distance between two probability distributions.
static double	Ms_cramer_von_mises.ms_cramer_von_mises(Matrix XX, Matrix YY)	Cramer-von Mises distance between two empirical distributions.
static double	Ms_czekanowski.ms_czekanowski(Matrix P, Matrix Q)	Czekanowski distance between two probability distributions.
static double	Ms_dice.ms_dice(Matrix P, Matrix Q)	Dice distance between two probability distributions.
static double	Ms_divergence.ms_divergence(Matrix P, Matrix Q)	Divergence distance between two probability distributions.
static double	Ms_entropy.ms_entropy(Matrix x)	Compute entropy z=H(x) of a discrete variable x.
static double	Ms_euclidean.ms_euclidean(Matrix P, Matrix Q)	Euclidean distance between two probability distributions.
static double	Ms_fidelity.ms_fidelity(Matrix P, Matrix Q)	Fidelity distance between two probability distributions.
static double	Ms_gower.ms_gower(Matrix P, Matrix Q)	Gower distance between two probability distributions.
static double	Ms_harmonicmean.ms_harmonicmean(Matrix P, Matrix Q)	Harmonic mean distance between two probability distributions.
static double	Ms_hellinger.ms_hellinger(Matrix P, Matrix Q)	Hellinger distance between two probability distributions.
static double	Ms_intersection.ms_intersection(Matrix P, Matrix Q)	Intersection distance between two probability distributions.
static double	Ms_jaccard.ms_jaccard(Matrix P, Matrix Q)	Jaccard distance between two probability distributions.
static double	Ms_jeffreys.ms_jeffreys(Matrix P, Matrix Q)	Jeffreys divergence between two probability distributions.
static double	Ms_jensendifference.ms_jensendifference(Matrix P, Matrix Q)	Jensen difference divergence between two probability distributions.
static double	Ms_jensenshannon.ms_jensenshannon(Matrix P, Matrix Q)	Jensen-Shannon divergence between two probability distributions.
static double	Ms_jointentropy.ms_jointentropy(Matrix x, Matrix y)	Compute joint entropy z=H(x,y) of two discrete variables x and y.
static double	Ms_kdivergence.ms_kdivergence(Matrix P, Matrix Q)	K-divergence between two probability distributions.
static double	Ms_kolmogorov_smirnov.ms_kolmogorov_smirnov(Matrix XX, Matrix YY)	Kolmogorov-Smirnov distance between two empirical distributions.
static double	Ms_kuiper.ms_kuiper(Matrix XX, Matrix YY)	Kuiper distance between two empirical distributions.
static double	Ms_kulczynskid.ms_kulczynskid(Matrix P, Matrix Q)	Kulczynski d distance between two probability distributions.
static double	Ms_kulczynskis.ms_kulczynskis(Matrix P, Matrix Q)	Kulczynski s distance between two probability distributions.
static double	Ms_kullbackleibler.ms_kullbackleibler(Matrix P, Matrix Q)	Kullback-Leibler divergence between two probability distributions.
static double	Ms_kumarhassebrook.ms_kumarhassebrook(Matrix P, Matrix Q)	Kumar-Hassebrook distance between two probability distributions.
static double	Ms_kumarjohnson.ms_kumarjohnson(Matrix P, Matrix Q)	Kumar-Johnson distance between two probability distributions.
static double	Ms_lorentzian.ms_lorentzian(Matrix P, Matrix Q)	Lorentzian distance between two probability distributions.
static double	Ms_matusita.ms_matusita(Matrix P, Matrix Q)	Matusita distance between two probability distributions.
static double	Ms_minkowski.ms_minkowski(Matrix P, Matrix Q, double p)	Minkowski distance between two probability distributions.
static double	Ms_motyka.ms_motyka(Matrix P, Matrix Q)	Motyka distance between two probability distributions.
static double	Ms_mutinfo.ms_mutinfo(Matrix x, Matrix y)	Compute mutual information I(x,y) of two discrete variables x and y.
static double	Ms_neymanchisquared.ms_neymanchisquared(Matrix P, Matrix Q)	Neyman chi-squared distance between two probability distributions.
static double	Ms_nmi.ms_nmi(Matrix x, Matrix y)	Compute normalized mutual information I(x,y)/sqrt(H(x)*H(y)) of two discrete variables x and y.
static double	Ms_nvi.ms_nvi(Matrix x, Matrix y)	Compute normalized variation information z=(1-I(x,y)/H(x,y)) of two discrete variables x and y.
static double	Ms_pearsonchisquared.ms_pearsonchisquared(Matrix P, Matrix Q)	Pearson chi-squared distance between two probability distributions.
static double	Ms_probsymmchisquared.ms_probsymmchisquared(Matrix P, Matrix Q)	Probabilistic symmetry chi-squared distance between two probability distributions.
static double	Ms_product.ms_product(Matrix P, Matrix Q)	Product distance between two probability distributions.
static double	Ms_relatentropy.ms_relatentropy(Matrix x, Matrix y)	Compute relative entropy (KL divergence) z=KL(p(x)||p(y)) of two discrete variables x and y.
static double	Ms_ruzicka.ms_ruzicka(Matrix P, Matrix Q)	Ruzicka distance between two probability distributions.
static double	Ms_soergel.ms_soergel(Matrix P, Matrix Q)	Soergel distance between two probability distributions.
static double	Ms_sorensen.ms_sorensen(Matrix P, Matrix Q)	Sorensen distance between two probability distributions.
static double	Ms_squaredchisquared.ms_squaredchisquared(Matrix P, Matrix Q)	Squared chi-squared distance between two probability distributions.
static double	Ms_squaredchord.ms_squaredchord(Matrix P, Matrix Q)	Squared chord distance between two probability distributions.
static double	Ms_squaredeuclidean.ms_squaredeuclidean(Matrix P, Matrix Q)	Squared Euclidean distance between two probability distributions.
static double	Ms_taneja.ms_taneja(Matrix P, Matrix Q)	Taneja distance between two probability distributions.
static double	Ms_tanimoto.ms_tanimoto(Matrix P, Matrix Q)	Tanimoto distance between two probability distributions.
static double	Ms_topsoe.ms_topsoe(Matrix P, Matrix Q)	Topsoe distance between two probability distributions.
static double	Ms_wasserstein.ms_wasserstein(Matrix XX, Matrix YY)	Wasserstein distance (Earth Mover's Distance) between two empirical distributions.
static double	Ms_wavehegdes.ms_wavehegdes(Matrix P, Matrix Q)	Wave-Hedges distance between two probability distributions.

Uses of Matrix in jline.api.nc

Methods in jline.api.nc that return Matrix

Modifier and Type	Method	Description
Matrix	MeOqnResult.getCa()
Matrix	MeOqnResult.getCd()
Matrix	MeOqnResult.getL()
Matrix	MeOqnResult.getLambda()
Matrix	MeOqnResult.getRho()
Matrix	MeOqnResult.getW()

Methods in jline.api.nc with parameters of type Matrix

Modifier and Type	Method	Description
static MeOqnResult	Me_oqn.me_oqn(int M, int R, Matrix lambda0, Matrix Ca0, Matrix mu, Matrix Cs, Matrix[][] P)
static MeOqnResult	Me_oqn.me_oqn(int M, int R, Matrix lambda0, Matrix Ca0, Matrix mu, Matrix Cs, Matrix[][] P, MeOqnOptions options)	Maximum Entropy algorithm for Open Queueing Networks.

Constructors in jline.api.nc with parameters of type Matrix

Modifier	Constructor	Description
	MeOqnResult(Matrix L, Matrix W, Matrix Ca, Matrix Cd, Matrix lambda, Matrix rho)

Uses of Matrix in jline.api.npfqn

Methods in jline.api.npfqn with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.npfqnNonexpApprox	Npfqn_nonexp_approx.npfqn_nonexp_approx(String method, NetworkStruct sn, Matrix ST, Matrix V, Matrix SCV, Matrix Tin, Matrix Uin, Matrix gamma, Matrix nservers)	Approximates non-product-form queueing networks using the specified method.
static MatrixCell	Npfqn_traffic_merge_cs.npfqn_traffic_merge_cs(Map<Integer,MatrixCell> MMAPs, Matrix prob)
static MatrixCell	Npfqn_traffic_merge_cs.npfqn_traffic_merge_cs(Map<Integer,MatrixCell> MMAPs, Matrix prob, String config)	Merges MMAP traffic flows with class switching.
static Map<Integer,MatrixCell>	Npfqn_traffic_split_cs.npfqn_traffic_split_cs(MatrixCell MMAP, Matrix P)	Splits MMAP traffic flows with class switching.

Uses of Matrix in jline.api.pfqn

Methods in jline.api.pfqn that return Matrix

Modifier and Type	Method	Description
Matrix	PfqnUniqueResult.getGamma_unique()
Matrix	PfqnUniqueResult.getL_unique()
Matrix	PfqnUniqueResult.getMi()
Matrix	PfqnUniqueResult.getMu_unique()
static Matrix	Pfqn_replicas.pfqn_combine_mi(Matrix mi, int[] mapping, int M_unique)	Combine user-provided multiplicity vector with detected replica multiplicity.

Methods in jline.api.pfqn that return types with arguments of type Matrix

Modifier and Type	Method	Description
static kotlin.Triple<Matrix,Matrix,Matrix>	Pfqn_replicas.pfqn_expand(Matrix QN, Matrix UN, Matrix CN, int[] mapping)	Expand per-station metrics from reduced model to original dimensions.
static kotlin.Triple<Matrix,Matrix,Matrix>	Pfqn_replicas.pfqn_expand(Matrix QN, Matrix UN, Matrix CN, int[] mapping)	Expand per-station metrics from reduced model to original dimensions.
static kotlin.Triple<Matrix,Matrix,Matrix>	Pfqn_replicas.pfqn_expand(Matrix QN, Matrix UN, Matrix CN, int[] mapping)	Expand per-station metrics from reduced model to original dimensions.

Methods in jline.api.pfqn with parameters of type Matrix

Modifier and Type	Method	Description
static Matrix	Pfqn_replicas.pfqn_combine_mi(Matrix mi, int[] mapping, int M_unique)	Combine user-provided multiplicity vector with detected replica multiplicity.
static kotlin.Triple<Matrix,Matrix,Matrix>	Pfqn_replicas.pfqn_expand(Matrix QN, Matrix UN, Matrix CN, int[] mapping)	Expand per-station metrics from reduced model to original dimensions.
static Ret.pfqnHarelBounds	Pfqn_harel_bounds.pfqn_harel_bounds(Matrix rho, int N)
static Ret.pfqnHarelBounds	Pfqn_harel_bounds.pfqn_harel_bounds(Matrix rho, int N, double Z)
static Ret.pfqnHarelBounds	Pfqn_harel_bounds.pfqn_harel_bounds(Matrix rho, int N, double Z, Integer maxUB)
static double	Pfqn_harel_bounds.pfqn_harel_lb(Matrix rho, int N)
static double	Pfqn_harel_bounds.pfqn_harel_lb(Matrix rho, int N, double Z)
static double	Pfqn_harel_bounds.pfqn_harel_ub(Matrix rho, int N, int n)
static double	Pfqn_harel_bounds.pfqn_harel_ub(Matrix rho, int N, int n, double Z)
static double	Pfqn_joint.pfqn_joint(Matrix n, Matrix L, Matrix N)
static double	Pfqn_joint.pfqn_joint(Matrix n, Matrix L, Matrix N, Matrix Z)
static double	Pfqn_joint.pfqn_joint(Matrix n, Matrix L, Matrix N, Matrix Z, Double lGN)	Compute the joint queue-length probability for vector n
static PfqnUniqueResult	Pfqn_replicas.pfqn_unique(Matrix L)
static PfqnUniqueResult	Pfqn_replicas.pfqn_unique(Matrix L, Matrix mu)
static PfqnUniqueResult	Pfqn_replicas.pfqn_unique(Matrix L, Matrix mu, Matrix gamma)	Consolidate replicated stations into unique stations with multiplicity.

Constructors in jline.api.pfqn with parameters of type Matrix

Modifier	Constructor	Description
	PfqnUniqueResult(Matrix L_unique, Matrix mu_unique, Matrix gamma_unique, Matrix mi, int[] mapping)

Uses of Matrix in jline.api.pfqn.lcfs

Fields in jline.api.pfqn.lcfs declared as Matrix

Modifier and Type	Field	Description
final Matrix[]	Pfqn_lcfsqn_nc.LcfsqnNcResult.Ax

Methods in jline.api.pfqn.lcfs that return Matrix

Modifier and Type	Method	Description
Matrix	LcfsqnMvaResult.getB()
Matrix	LcfsqnMvaResult.getQ()
Matrix	LcfsqnMvaResult.getT()
Matrix	LcfsqnMvaResult.getU()

Methods in jline.api.pfqn.lcfs with parameters of type Matrix

Modifier and Type	Method	Description
static LcfsqnCaResult	Pfqn_lcfsqn_ca.pfqn_lcfsqn_ca(Matrix alpha, Matrix beta)
static LcfsqnCaResult	Pfqn_lcfsqn_ca.pfqn_lcfsqn_ca(Matrix alpha, Matrix beta, Matrix N)	Convolution algorithm for multiclass LCFS queueing networks.
static LcfsqnMvaResult	Pfqn_lcfsqn_mva.pfqn_lcfsqn_mva(Matrix alpha, Matrix beta)
static LcfsqnMvaResult	Pfqn_lcfsqn_mva.pfqn_lcfsqn_mva(Matrix alpha, Matrix beta, Matrix N)
static Pfqn_lcfsqn_nc.LcfsqnNcResult	Pfqn_lcfsqn_nc.pfqn_lcfsqn_nc(Matrix alpha, Matrix beta, Matrix N)	Normalizing constant for multiclass LCFS queueing networks.

Constructors in jline.api.pfqn.lcfs with parameters of type Matrix

Modifier	Constructor	Description
	LcfsqnMvaResult(Matrix T, Matrix Q, Matrix U, Matrix B)
	LcfsqnNcResult(double G, Matrix[] Ax)

Uses of Matrix in jline.api.pfqn.ld

Methods in jline.api.pfqn.ld that return Matrix

Modifier and Type	Method	Description
static Matrix	Pfqn_ljdfun.ljd_delinearize(int idx, Matrix cutoffs)	Convert linearized index back to per-class population vector
static Matrix	Pfqn_cdfun.pfqn_cdfun(Matrix nvec, List<SerializableFunction<Matrix,Double>> cdscaling, int M)	Evaluate class-dependent (CD) scaling function.
static Matrix	Pfqn_ljdfun.pfqn_ljdfun(Matrix nvec, List<Matrix> ljdscaling, List<Matrix> ljdcutoffs, int M, Matrix nservers)	Evaluate limited joint-dependent (LJD) function
static Matrix	Pfqn_lldfun.pfqn_lldfun(Matrix n, Matrix lldscaling, Matrix nservers)	Evaluate limited-load dependent (LLD) function.
static Matrix	Pfqn_mu_ms.pfqn_mu_ms(int N, int m, int c)
static Matrix	Pfqn_mushift.pfqn_mushift(Matrix mu, int k)	Shifts a load-dependent scaling vector by one position

Methods in jline.api.pfqn.ld with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.pfqnNc	Pfqn_ncld.compute_norm_const_ld(Matrix L, Matrix N, Matrix Z, Matrix mu, SolverOptions options)
static double	Pfqn_ljdfun.ljcd_interpolate(Matrix nvec, Matrix cutoffs, Matrix table, int K)	Multi-linear interpolation for LJCD scaling tables.
static Matrix	Pfqn_ljdfun.ljd_delinearize(int idx, Matrix cutoffs)	Convert linearized index back to per-class population vector
static int	Pfqn_ljdfun.ljd_linearize(Matrix nvec, Matrix cutoffs)	Convert per-class population vector to linearized index (0-indexed)
static Ret.pfqnAB	Pfqn_ab.pfqn_ab(Matrix D, Matrix N, Matrix S, List<SchedStrategy> sched)
static Matrix	Pfqn_cdfun.pfqn_cdfun(Matrix nvec, List<SerializableFunction<Matrix,Double>> cdscaling, int M)	Evaluate class-dependent (CD) scaling function.
static Ret.pfqnComomrmLd	Pfqn_comomrm_ld.pfqn_comomrm_ld(Matrix Lin, Matrix Nin, Matrix Zin, Matrix muIn, SolverOptions options)	Run the COMOM normalizing constant solution method on a repairman model.
static double[]	Pfqn_conv.pfqn_conv(Matrix L, int[] N, double[] Z, Matrix mu, List<List<Matrix>> ljcdscaling, List<Matrix> ljcdcutoffs)	Multichain convolution for LJCD networks.
static Ret.pfqnFnc	Pfqn_fnc.pfqn_fnc(Matrix alpha)	Compute scaling factor of a load-dependent functional server use to calculate the mean
static Ret.pfqnFnc	Pfqn_fnc.pfqn_fnc(Matrix alpha, Matrix c)	Compute scaling factor of a load-dependent functional server use to calculate the mean instantiated with scaling constant c.
static Ret.pfqnNc	Pfqn_gld.pfqn_gld(Matrix L, Matrix N, Matrix mu, SolverOptions options)	Compute the normalizing constant of a single-class load-dependent closed queueing network model
static Ret.pfqnNcComplex	Pfqn_gld_complex.pfqn_gld_complex(ComplexMatrix L, Matrix N, Matrix mu, SolverOptions options)	Compute the normalizing constant of a single-class load-dependent closed queueing network model with complex demands.
static Ret.pfqnNc	Pfqn_gldsingle.pfqn_gldsingle(Matrix L, Matrix N, Matrix mu, SolverOptions options)	Auxiliary function used by pfqn_gld to compute the normalizing constant in a single-class load-dependent model.
static Ret.pfqnNcComplex	Pfqn_gldsingle_complex.pfqn_gldsingle_complex(ComplexMatrix L, Matrix N, Matrix mu, SolverOptions options)	Auxiliary function used by pfqn_gld to compute the normalizing constant in a single-class load-dependent model with complex demands.
static Matrix	Pfqn_ljdfun.pfqn_ljdfun(Matrix nvec, List<Matrix> ljdscaling, List<Matrix> ljdcutoffs, int M, Matrix nservers)	Evaluate limited joint-dependent (LJD) function
static Matrix	Pfqn_lldfun.pfqn_lldfun(Matrix n, Matrix lldscaling, Matrix nservers)	Evaluate limited-load dependent (LLD) function.
static double	Pfqn_mu_ms.pfqn_mu_ms_gnaux(int n, int m, int c, Matrix g)
static Matrix	Pfqn_mushift.pfqn_mushift(Matrix mu, int k)	Shifts a load-dependent scaling vector by one position
static Ret.pfqnMVALD	Pfqn_mvald.pfqn_mvald(Matrix L, Matrix N, Matrix Z, Matrix mu)
static Ret.pfqnMVALD	Pfqn_mvald.pfqn_mvald(Matrix L, Matrix N, Matrix Z, Matrix mu, boolean stabilize)
static Ret.pfqnMVA	Pfqn_mvaldms.pfqn_mvaldms(Matrix lambda, Matrix D, Matrix N, Matrix Z, Matrix S)	Wrapper for pfqn_mvaldmx that adjusts utilizations to account for multiservers.
static Ret.pfqnMVALDMX	Pfqn_mvaldmx.pfqn_mvaldmx(Matrix lambda, Matrix D, Matrix N, Matrix Z, Matrix mu, Matrix S)	MVA method for mixed queueing networks with load-dependent nodes.
static Ret.pfqnMVALDMXEC	Pfqn_mvaldmx_ec.pfqn_mvaldmx_ec(Matrix lambda, Matrix D, Matrix mu)	Auxiliary function used by pfqn_mvaldmx to compute the EC terms.
static Ret.pfqnNc	Pfqn_ncld.pfqn_ncld(Matrix L, Matrix N, Matrix Z, Matrix mu, SolverOptions options)
static Ret.pfqnProcomom2	Pfqn_procomom2.pfqn_procomom2(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnProcomom2	Pfqn_procomom2.pfqn_procomom2(Matrix L, Matrix N, Matrix Z, Matrix mu)
static Ret.pfqnProcomom2	Pfqn_procomom2.pfqn_procomom2(Matrix L, Matrix N, Matrix Z, Matrix mu, Integer m)	Compute marginal state probabilities for the queue in a model consisting of a queueing station and a delay station only.
static Ret.pfqnSchmidt	Pfqn_schmidt.pfqn_schmidt(Matrix D, Matrix N, Matrix S, List<SchedStrategy> sched)
static double	Pfqn_xia.pfqn_xia(Matrix L, int N, Matrix s, SolverOptions options)

Method parameters in jline.api.pfqn.ld with type arguments of type Matrix

Modifier and Type	Method	Description
static Matrix	Pfqn_cdfun.pfqn_cdfun(Matrix nvec, List<SerializableFunction<Matrix,Double>> cdscaling, int M)	Evaluate class-dependent (CD) scaling function.
static double[]	Pfqn_conv.pfqn_conv(Matrix L, int[] N, double[] Z, Matrix mu, List<List<Matrix>> ljcdscaling, List<Matrix> ljcdcutoffs)	Multichain convolution for LJCD networks.
static Matrix	Pfqn_ljdfun.pfqn_ljdfun(Matrix nvec, List<Matrix> ljdscaling, List<Matrix> ljdcutoffs, int M, Matrix nservers)	Evaluate limited joint-dependent (LJD) function

Uses of Matrix in jline.api.pfqn.mva

Fields in jline.api.pfqn.mva declared as Matrix

Modifier and Type	Field	Description
final Matrix	Pfqn_sqni.PfqnSqniResult.Q
final Matrix	Pfqn_sqni.PfqnSqniResult.U
final Matrix	Pfqn_sqni.PfqnSqniResult.X

Methods in jline.api.pfqn.mva that return Matrix

Modifier and Type	Method	Description
Matrix	Pfqn_qd.BetaFunction.apply(Matrix Akr)
Matrix	Pfqn_qd.GammaFunction.apply(Matrix A)

Methods in jline.api.pfqn.mva with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.pfqnAMVAMS	Pfqn_ab_amva.ab_amva(Matrix serviceTimes, Matrix N, Matrix V, Matrix nservers, List<SchedStrategy> schedStrategies, boolean fcfsSchmidt, String marginalProbMethod)
static Ret.pfqnAMVA	Pfqn_ab_amva.ab_linearizer(int K, int M, Matrix population, Matrix nservers, List<SchedStrategy> type, Matrix v, Matrix s, boolean fcfsSchmidt, String marginalProbMethod)
Matrix	Pfqn_qd.BetaFunction.apply(Matrix Akr)
Matrix	Pfqn_qd.GammaFunction.apply(Matrix A)
static Map<Integer,Double>	Pfqn_ab_amva.findMarginalProbs(double avgJobs, int numServers, Matrix population, int classIdx, String marginalProbMethod)
static Ret.pfqnAMVA	Pfqn_ab_amva.pfqn_ab_core(int K, int M, Matrix population, Matrix nservers, List<SchedStrategy> type, Matrix v, Matrix s, int maxiter, double[][][] D, Matrix lIn, boolean fcfsSchmidt, String marginalProbMethod)
static Ret.pfqnAMVA	Pfqn_aql.pfqn_aql(Matrix L, Matrix N)
static Ret.pfqnAMVA	Pfqn_aql.pfqn_aql(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnAMVA	Pfqn_aql.pfqn_aql(Matrix Lin, Matrix N, Matrix Zin, double tol, int maxiter)
static Ret.pfqnAMVA	Pfqn_aql.pfqn_aql(Matrix L, Matrix N, Matrix Z, int maxiter)
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N)
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter)
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter, Matrix QN0)
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter, Matrix QN0, SchedStrategy[] type)
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter, Matrix QN0, SchedStrategy[] type, Matrix weight)	Bard-Schweitzer approximate mean value analysis algorithm with optional weighted priorities.
static Ret.pfqnAMVA	Pfqn_bs.pfqn_bs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter, Matrix QN0, Matrix weight)	Bard-Schweitzer approximate mean value analysis algorithm with weighted priorities.
static Ret.pfqnAMVA	Pfqn_bsfcfs.pfqn_bsfcfs(Matrix L, Matrix N)
static Ret.pfqnAMVA	Pfqn_bsfcfs.pfqn_bsfcfs(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnAMVA	Pfqn_bsfcfs.pfqn_bsfcfs(Matrix L, Matrix N, Matrix Z, double tol)
static Ret.pfqnAMVA	Pfqn_bsfcfs.pfqn_bsfcfs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter)
static Ret.pfqnAMVA	Pfqn_bsfcfs.pfqn_bsfcfs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter, Matrix QN0)
static Ret.pfqnAMVA	Pfqn_bsfcfs.pfqn_bsfcfs(Matrix L, Matrix N, Matrix Z, double tol, int maxiter, Matrix QN0, Matrix weight)	Bard-Schweitzer approximate MVA for FCFS scheduling with weighted priorities.
static Ret.pfqnAMVAMS	Pfqn_conwayms.pfqn_conwayms(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnAMVAMS	Pfqn_conwayms.pfqn_conwayms(Matrix L, Matrix N, Matrix Z, int[] nservers)
static Ret.pfqnAMVAMS	Pfqn_conwayms.pfqn_conwayms(Matrix L, Matrix N, Matrix Z, int[] nservers, SchedStrategy[] type, double tol, int maxiter)
static Ret.LinearizerResult	Pfqn_conwayms.pfqn_conwayms_core(Matrix L, int M, int R, Matrix N_1, Matrix Z, int[] nservers, Matrix Q, Matrix P, Matrix PB, MatrixCell Delta, SchedStrategy[] type, double tol, int maxiter)
static Ret.pfqnEstimate	Pfqn_conwayms.pfqn_conwayms_estimate(int M, int R, Matrix N_1, int[] nservers, Matrix Q, Matrix P, Matrix PB, MatrixCell Delta, Matrix W)
static Ret.LinearizerResult	Pfqn_conwayms.pfqn_conwayms_forwardmva(Matrix L, int M, int R, Matrix N_1, Matrix Z, int[] nservers, SchedStrategy[] type, MatrixCell Q_1, MatrixCell P_1, Matrix PB_1, Matrix T_1)
static Ret.pfqnAMVA	Pfqn_egflinearizer.pfqn_egflinearizer(Matrix L, Matrix N, Matrix Z, SchedStrategy[] type, double tol, int maxiter, Matrix alpha)
static Ret.pfqnAMVA	Pfqn_gflinearizer.pfqn_gflinearizer(Matrix L, Matrix N, Matrix Z, SchedStrategy[] type, double tol, int maxiter, double alpha)	General-form linearizer algorithm
static Ret.pfqnAMVA	Pfqn_linearizer.pfqn_linearizer(Matrix L, Matrix N, Matrix Z, SchedStrategy[] type)
static Ret.pfqnAMVA	Pfqn_linearizer.pfqn_linearizer(Matrix L, Matrix N, Matrix Z, SchedStrategy[] type, double tol)
static Ret.pfqnAMVA	Pfqn_linearizer.pfqn_linearizer(Matrix L, Matrix N, Matrix Z, SchedStrategy[] type, double tol, int maxiter)	Linearizer approximate mean value analysis algorithm
static Ret.pfqnAMVAMS	Pfqn_linearizerms.pfqn_linearizerms(Matrix L, Matrix N, Matrix nservers)
static Ret.pfqnAMVAMS	Pfqn_linearizerms.pfqn_linearizerms(Matrix L, Matrix N, Matrix Z, Matrix nservers)
static Ret.pfqnAMVAMS	Pfqn_linearizerms.pfqn_linearizerms(Matrix L, Matrix N, Matrix Z, Matrix nservers, List<SchedStrategy> type)
static Ret.pfqnAMVAMS	Pfqn_linearizerms.pfqn_linearizerms(Matrix L, Matrix N, Matrix Z, Matrix nservers, List<SchedStrategy> type, double tol, int maxiter)
static Ret.pfqnAMVA	Pfqn_linearizermx.pfqn_linearizermx(Matrix lambda, Matrix L, Matrix N, Matrix Z, Matrix nservers, SchedStrategy[] type, double tol, int maxiter, String method)	Linearizer method for mixed models with multi-server stations.
static Ret.pfqnAMVA	Pfqn_linearizerpp.pfqn_linearizerpp(Matrix L, Matrix N, int level)
static Ret.pfqnAMVA	Pfqn_linearizerpp.pfqn_linearizerpp(Matrix L, Matrix N, Matrix Z, int level)
static Ret.pfqnAMVA	Pfqn_linearizerpp.pfqn_linearizerpp(Matrix L, Matrix N, Matrix Z, int level, double tol)
static Ret.pfqnAMVA	Pfqn_linearizerpp.pfqn_linearizerpp(Matrix L, Matrix N, Matrix Z, int level, double tol, int maxiter)
static Ret.pfqnAMVA	Pfqn_linearizerpp.pfqn_linearizerpp(Matrix L, Matrix N, Matrix Z, int level, double tol, int maxiter, int flag)
static Ret.pfqnMVA	Pfqn_mva.pfqn_mva(Matrix L, Matrix N)
static Ret.pfqnMVA	Pfqn_mva.pfqn_mva(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnMVA	Pfqn_mva.pfqn_mva(Matrix L, Matrix N, Matrix Z, Matrix mi)	Mean Value Analysis (MVA) Algorithm for closed Product-Form Queueing Networks.
static Ret.pfqnMVA	Pfqn_mvams.pfqn_mvams(Matrix lambda, Matrix L, Matrix N, Matrix mi, Matrix S)
static Ret.pfqnMVA	Pfqn_mvams.pfqn_mvams(Matrix lambda, Matrix L, Matrix N, Matrix Z, Matrix mi, Matrix S)	General purpose script to handle mixed Query Networks with multiserver nodes.
static Ret.pfqnMVA	Pfqn_mvamx.pfqn_mvamx(Matrix lambda, Matrix D, Matrix N, Matrix mi)
static Ret.pfqnMVA	Pfqn_mvamx.pfqn_mvamx(Matrix lambda, Matrix D, Matrix N, Matrix Z, Matrix mi)	Mean Value Analysis (MVA) method for open and mixed queueing networks with no multi-server nodes.
static Ret.pfqnQd	Pfqn_qd.pfqn_qd(Matrix L, Matrix N)
static Ret.pfqnQd	Pfqn_qd.pfqn_qd(Matrix L, Matrix N, Pfqn_qd.GammaFunction ga)
static Ret.pfqnQd	Pfqn_qd.pfqn_qd(Matrix L, Matrix N, Pfqn_qd.GammaFunction ga, Pfqn_qd.BetaFunction be)
static Ret.pfqnQd	Pfqn_qd.pfqn_qd(Matrix L, Matrix N, Pfqn_qd.GammaFunction ga, Pfqn_qd.BetaFunction be, Matrix Q0)	Queue-Dependent (QD) approximate MVA solver
static double	Pfqn_qzgblow.pfqn_qzgblow(Matrix L, double N, double Z, int i)	Computes the lower Geometric Bound (GB) for the queue length of the given closed single-class queueing networks
static double	Pfqn_qzgbup.pfqn_qzgbup(Matrix L, double N, double Z, int i)	Computes the upper Geometric Bound (GB) for the queue length of the given closed single-class queueing networks.
static Ret.pfqnAMVASchmidt	Pfqn_schmidt_amva.pfqn_schmidt(Matrix rates, Matrix N, Matrix S, Matrix v, List<SchedStrategy> sched)
static Ret.pfqnAMVASchmidt	Pfqn_schmidt_amva.pfqn_schmidt_ext(Matrix rates, Matrix N, Matrix S, Matrix v, List<SchedStrategy> sched)
static Pfqn_sqni.PfqnSqniResult	Pfqn_sqni.pfqn_sqni(Matrix N, Matrix L, Matrix Z)
static double	Pfqn_xzabalow.pfqn_xzabalow(Matrix L, double N, double Z)	Computes the low ABA for the throughput of the given closed single-class queueing networks
static double	Pfqn_xzabaup.pfqn_xzabaup(Matrix L, double N, double Z)	Computes the upper ABA for the throughput of the given closed single-class queueing networks
static double	Pfqn_xzgsblow.pfqn_xzgsblow(Matrix L, double N, double Z)	Computes the lower Geometric Square-Root Bound (GSB) for the throughput of the given closed single-class queueing networks.
static double	Pfqn_xzgsbup.pfqn_xzgsbup(Matrix L, double N, double Z)	Computes the upper Geometric Square-Root Bound (GSB) for the throughput of the given closed single-class queueing networks.

Constructors in jline.api.pfqn.mva with parameters of type Matrix

Modifier	Constructor	Description
	PfqnSqniResult(Matrix Q, Matrix U, Matrix X)

Uses of Matrix in jline.api.pfqn.nc

Methods in jline.api.pfqn.nc that return Matrix

Modifier and Type	Method	Description
static Matrix	Pfqn_le_hessian.pfqn_le_hessian(Matrix L, Matrix N, Matrix u0)	Auxiliary function to compute the Hessian used in the logistic expansion method.
static Matrix	Pfqn_nca.pfqn_nca(Matrix L, int N, Matrix alpha)
static Matrix[][]	Pfqn_stdf.pfqn_stdf(Matrix L, Matrix N, Matrix Z, Matrix S, Matrix fcfsNodes, Matrix rates, Matrix tset)	Sojourn time distribution function at multiserver FCFS nodes (McKenna 1987 JACM).
static Matrix[][]	Pfqn_stdf_heur.pfqn_stdf_heur(Matrix L, Matrix N, Matrix Z, Matrix S, Matrix fcfsNodes, Matrix rates, Matrix tset)	Heuristic sojourn time distribution analysis at multiserver FCFS nodes.

Methods in jline.api.pfqn.nc that return types with arguments of type Matrix

Modifier and Type	Method	Description
static SerializableFunction<Matrix,ComplexMatrix>	Pfqn_nrl.infradius_h(Matrix L, Matrix N, Matrix alpha)
static SerializableFunction<Matrix,ComplexMatrix>	Pfqn_nrp.infradius_hnorm(Matrix L, Matrix N, Matrix alpha)
static kotlin.jvm.functions.Function1<Matrix,org.apache.commons.math3.complex.Complex>	Pfqn_nrl.nrl_h(Matrix L, Matrix tsubtb, double Nt, Matrix alpha)
static kotlin.jvm.functions.Function1<Matrix,org.apache.commons.math3.complex.Complex>	Pfqn_nrp.nrp_h(Matrix L, Matrix tsubtb, double Nt, Matrix alpha)

Methods in jline.api.pfqn.nc with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.pfqnNcXQ	Pfqn_nc.compute_norm_const(Matrix L, Matrix N, Matrix Z, SolverOptions options)
static SerializableFunction<Matrix,ComplexMatrix>	Pfqn_nrl.infradius_h(Matrix L, Matrix N, Matrix alpha)
static SerializableFunction<Matrix,ComplexMatrix>	Pfqn_nrp.infradius_hnorm(Matrix L, Matrix N, Matrix alpha)
static kotlin.jvm.functions.Function1<Matrix,org.apache.commons.math3.complex.Complex>	Pfqn_nrl.nrl_h(Matrix L, Matrix tsubtb, double Nt, Matrix alpha)
static kotlin.jvm.functions.Function1<Matrix,org.apache.commons.math3.complex.Complex>	Pfqn_nrp.nrp_h(Matrix L, Matrix tsubtb, double Nt, Matrix alpha)
static Ret.pfqnNc	Pfqn_ca.pfqn_ca(Matrix L, Matrix N)
static Ret.pfqnNc	Pfqn_ca.pfqn_ca(Matrix L, Matrix N, Matrix Z)
static double	Pfqn_comom.pfqn_comom(Matrix L, Matrix N, Matrix Z, double atol)
static Ret.pfqnComomrm	Pfqn_comomrm.pfqn_comomrm(Matrix L, Matrix N, Matrix Z, Integer m, double atol)	Compute the normalizing constant of a repairmen model using COMOM
static Ret.pfqnComomrmMs	Pfqn_comomrm_ms.pfqn_comomrm_ms(Matrix L, Matrix N, Matrix Z, int S)
static Ret.pfqnComomrmMs	Pfqn_comomrm_ms.pfqn_comomrm_ms(Matrix L, Matrix N, Matrix Z, int m, int S)	Compute the normalizing constant of a multiserver repairman model using CoMoM.
static double	Pfqn_comomrm_orig.pfqn_comomrm_orig(Matrix L, Matrix N, Matrix Z)
static double	Pfqn_comomrm_orig.pfqn_comomrm_orig(Matrix L, Matrix N, Matrix Z, double atol)
static Ret.pfqnNc	Pfqn_cub.pfqn_cub(Matrix L, Matrix N, Matrix Z)	Cubature method to compute the normalizing constant of a load-independent closed queueing network model
static Ret.pfqnNc	Pfqn_cub.pfqn_cub(Matrix L, Matrix N, Matrix Z, int order, double atol)	Cubature method to compute the normalizing constant of a load-independent closed queueing network model
static double	Pfqn_grnmol.pfqn_grnmol(Matrix L, Matrix N)	Compute the normalizing constant using Grundmann-Moeller quadrature
static Ret.pfqnNc	Pfqn_kt.pfqn_kt(Matrix L, Matrix N, Matrix Z)	Knessl-Tier asymptotic expansion of the normalizing constant using the ray method.
static double	Pfqn_lap.pfqn_lap(Matrix L, Matrix N, Matrix Z)	Compute the Laplace approximation for the log normalizing constant.
static Ret.pfqnNc	Pfqn_le.pfqn_le(Matrix L, Matrix N)
static Ret.pfqnNc	Pfqn_le.pfqn_le(Matrix L, Matrix N, Matrix Z)	Logistic expansion method to compute the normalizing constant.
static Ret.pfqnLeFpi	Pfqn_le_fpi.pfqn_le_fpi(Matrix L, Matrix N)	Fixed-point iteration used in the logistic expansion method.
static Ret.pfqnLeFpiZ	Pfqn_le_fpiZ.pfqn_le_fpiZ(Matrix L, Matrix N, Matrix Z)	Fixed-point iteration used in the logistic expansion method in models with delays.
static Matrix	Pfqn_le_hessian.pfqn_le_hessian(Matrix L, Matrix N, Matrix u0)	Auxiliary function to compute the Hessian used in the logistic expansion method.
static Ret.pfqnNc	Pfqn_ls.pfqn_ls(Matrix L, Matrix N, long I)
static Ret.pfqnNc	Pfqn_ls.pfqn_ls(Matrix L, Matrix N, long I, long seed)
static Ret.pfqnNc	Pfqn_ls.pfqn_ls(Matrix L, Matrix N, Matrix Z, long I)
static Ret.pfqnNc	Pfqn_ls.pfqn_ls(Matrix L, Matrix N, Matrix Z, long I, long seed)	Logistic sampling method to compute the normalizing constant.
static Ret.pfqnNc	Pfqn_mci.pfqn_mci(Matrix D, Matrix N, Matrix Z, int I, String variant)
static Ret.pfqnNc	Pfqn_mmint2.pfqn_mmint2(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnNc	Pfqn_mmint2_gausslaguerre.pfqn_mmint2_gausslaguerre(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnNc	Pfqn_mmint2_gausslaguerre.pfqn_mmint2_gausslaguerre(Matrix L, Matrix N, Matrix Z, int m)
static Ret.pfqnNc	Pfqn_mmint2_gausslegendre.pfqn_mmint2_gausslegendre(Matrix L, Matrix N, Matrix Z, Integer m)	Compute the normalizing constant of a repairmen model using Gauss-Legendre integration.
static Ret.pfqnNc	Pfqn_mmsample2.pfqn_mmsample2(Matrix L, Matrix N, Matrix Z, int samples)
static Ret.pfqnMom	Pfqn_mom.pfqn_mom(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnNcXQ	Pfqn_nc.pfqn_nc(Matrix lambda, Matrix L, Matrix N, Matrix Z, SolverOptions options)
static Ret.pfqnNcSanitize	Pfqn_nc_sanitize.pfqn_nc_sanitize(Matrix lambda, Matrix L, Matrix N, Matrix Z, double atol)	Sanitizes product-form model parameters to avoid degeneracies.
static Matrix	Pfqn_nca.pfqn_nca(Matrix L, int N, Matrix alpha)
static double	Pfqn_nrl.pfqn_nrl(Matrix Lin, Matrix N, Matrix Z, Matrix alphaIn, SolverOptions options)
static double	Pfqn_nrp.pfqn_nrp(Matrix Lin, Matrix N, Matrix Z, Matrix alphaIn, SolverOptions options)
static Ret.pfqnNc	Pfqn_panacea.pfqn_panacea(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnNc	Pfqn_panacea.pfqn_panacea(Matrix L, Matrix N, Matrix Z, SolverOptions options)	Compute the PANACEA approximation
static double	Pfqn_pff_delay.pfqn_pff_delay(Matrix Z, Matrix n)	Compute the product-form factor relatively to a Delay station.
static Ret.pfqnProcomom	Pfqn_procomom.pfqn_procomom(Matrix L, Matrix N)
static Ret.pfqnProcomom	Pfqn_procomom.pfqn_procomom(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnProcomom	Pfqn_procomom.pfqn_procomom(Matrix L, Matrix N, Matrix Z, double atol)
static Ret.pfqnNcXQ	Pfqn_propfair.pfqn_propfair(Matrix L, Matrix N, Matrix Z)	Compute the proportionally fair allocation approximation.
static Ret.pfqnRd	Pfqn_rd.pfqn_rd(Matrix L, Matrix N, Matrix Z, Matrix mu, SolverOptions options)
static Ret.pfqnNc	Pfqn_recal.pfqn_recal(Matrix L, Matrix N)	RECAL method to compute the normalizing constant of a load-independent closed queueing network model.
static Ret.pfqnNc	Pfqn_recal.pfqn_recal(Matrix L, Matrix N, Matrix Z)
static Ret.pfqnNc	Pfqn_recal.pfqn_recal(Matrix L, Matrix N, Matrix Z, Matrix m0)
static Matrix[][]	Pfqn_stdf.pfqn_stdf(Matrix L, Matrix N, Matrix Z, Matrix S, Matrix fcfsNodes, Matrix rates, Matrix tset)	Sojourn time distribution function at multiserver FCFS nodes (McKenna 1987 JACM).
static Matrix[][]	Pfqn_stdf_heur.pfqn_stdf_heur(Matrix L, Matrix N, Matrix Z, Matrix S, Matrix fcfsNodes, Matrix rates, Matrix tset)	Heuristic sojourn time distribution analysis at multiserver FCFS nodes.

Uses of Matrix in jline.api.qsys

Fields in jline.api.qsys declared as Matrix

Modifier and Type	Field	Description
final Matrix	QsysRetrialResult.pi

Methods in jline.api.qsys that return Matrix

Modifier and Type	Method	Description
Matrix	QsysRetrialResult.getPi()
Matrix	QsysMapDcResult.getQueueLengthDist()
Matrix	QsysMapPhResult.getQueueLengthDist()
Matrix	QsysMapPhResult.getQueueLengthMoments()
Matrix	QsysMapPhResult.getSojournTimeMoments()
Matrix	QsysMapDcResult.getWaitingTimeDist()

Methods in jline.api.qsys with parameters of type Matrix

Modifier and Type	Method	Description
static QsysRetrialResult	Qsys_bmapphnn_retrial.qsys_bmapphnn_retrial(Matrix[] D, Matrix beta, Matrix S, int N, double alpha, double gamma, double p, int R)
static QsysRetrialResult	Qsys_bmapphnn_retrial.qsys_bmapphnn_retrial(Matrix[] D, Matrix beta, Matrix S, int N, double alpha, double gamma, double p, int[] R)
static QsysRetrialResult	Qsys_bmapphnn_retrial.qsys_bmapphnn_retrial(Matrix[] D, Matrix beta, Matrix S, int N, double alpha, double gamma, double p, int[] R, int maxLevel)
static QsysRetrialResult	Qsys_bmapphnn_retrial.qsys_bmapphnn_retrial(Matrix[] D, Matrix beta, Matrix S, int N, double alpha, double gamma, double p, int[] R, int maxLevel, double tolerance, boolean verbose)
static QsysRetrialResult	Qsys_bmapphnn_retrial.qsys_bmapphnn_retrial(Matrix[] D, Matrix beta, Matrix S, int N, double alpha, double gamma, double p, int R, int maxLevel)
static QsysRetrialResult	Qsys_bmapphnn_retrial.qsys_bmapphnn_retrial(Matrix[] D, Matrix beta, Matrix S, int N, double alpha, double gamma, double p, int R, int maxLevel, double tolerance, boolean verbose)
static QsysMapDcResult	Qsys_mapd1.qsys_mapd1(Matrix D0, Matrix D1, double s)
static QsysMapDcResult	Qsys_mapd1.qsys_mapd1(Matrix D0, Matrix D1, double s, int maxNumComp)
static QsysMapDcResult	Qsys_mapd1.qsys_mapd1(Matrix D0, Matrix D1, double s, int maxNumComp, int numSteps)	Analyzes a MAP/D/1 queue (single server with deterministic service).
static QsysMapDcResult	Qsys_mapdc.qsys_mapdc(Matrix D0, Matrix D1, double s, int c)
static QsysMapDcResult	Qsys_mapdc.qsys_mapdc(Matrix D0, Matrix D1, double s, int c, int maxNumComp)
static QsysMapDcResult	Qsys_mapdc.qsys_mapdc(Matrix D0, Matrix D1, double s, int c, int maxNumComp, int numSteps)
static QsysMapDcResult	Qsys_mapdc.qsys_mapdc(Matrix D0, Matrix D1, double s, int c, int maxNumComp, int numSteps, int verbose)	Analyzes a MAP/D/c queue (multi-server with deterministic service).
static QsysMapPhResult	Qsys_mapg1.qsys_mapg1(Matrix D0, Matrix D1, double[] serviceMoments)
static QsysMapPhResult	Qsys_mapg1.qsys_mapg1(Matrix D0, Matrix D1, double[] serviceMoments, int numQLMoms)
static QsysMapPhResult	Qsys_mapg1.qsys_mapg1(Matrix D0, Matrix D1, double[] serviceMoments, int numQLMoms, int numQLProbs)
static QsysMapPhResult	Qsys_mapg1.qsys_mapg1(Matrix D0, Matrix D1, double[] serviceMoments, int numQLMoms, int numQLProbs, int numSTMoms)	Analyzes a MAP/G/1 queue.
static QsysMapPhResult	Qsys_mapg1.qsys_mapg1(Matrix D0, Matrix D1, double meanService, double cvService)	Analyzes a MAP/G/1 queue with service time specified as mean and CV.
static QsysMapPhResult	Qsys_mapm1.qsys_mapm1(Matrix D0, Matrix D1, double mu)
static QsysMapPhResult	Qsys_mapm1.qsys_mapm1(Matrix D0, Matrix D1, double mu, int maxNumComp)	Analyzes a MAP/M/1 queue (single server with exponential service).
static QsysMapPhResult	Qsys_mapmap1.qsys_mapmap1(Matrix C0, Matrix C1, Matrix D0, Matrix D1)
static QsysMapPhResult	Qsys_mapmap1.qsys_mapmap1(Matrix C0, Matrix C1, Matrix D0, Matrix D1, int numQLMoms, int numQLProbs, int numSTMoms)	Analyzes a MAP/MAP/1 queue.
static QsysMapPhResult	Qsys_mapmc.qsys_mapmc(Matrix D0, Matrix D1, double mu, int c)
static QsysMapPhResult	Qsys_mapmc.qsys_mapmc(Matrix D0, Matrix D1, double mu, int c, String mode, int maxNumComp)
static QsysMapPhResult	Qsys_mapmc.qsys_mapmc(Matrix D0, Matrix D1, double mu, int c, String mode, int maxNumComp, int verbose)	Analyzes a MAP/M/c queue (multi-server with exponential service).
static QsysMapPhResult	Qsys_mapph1.qsys_mapph1(Matrix D0, Matrix D1, Matrix sigma, Matrix S)
static QsysMapPhResult	Qsys_mapph1.qsys_mapph1(Matrix D0, Matrix D1, Matrix sigma, Matrix S, int numQLMoms)
static QsysMapPhResult	Qsys_mapph1.qsys_mapph1(Matrix D0, Matrix D1, Matrix sigma, Matrix S, int numQLMoms, int numQLProbs)
static QsysMapPhResult	Qsys_mapph1.qsys_mapph1(Matrix D0, Matrix D1, Matrix sigma, Matrix S, int numQLMoms, int numQLProbs, int numSTMoms)	Analyzes a MAP/PH/1 queue.
static Ret.qsys_prio	Qsys_mg1_fb.qsys_mg1_fb(Matrix lambda, Matrix mu, Matrix cs)	Analyzes an M/G/1 queueing system with FB (Feedback/LAS) scheduling.
static Ret.qsys_prio	Qsys_mg1_lrpt.qsys_mg1_lrpt(Matrix lambda, Matrix mu, Matrix cs)	Analyzes an M/G/1 queueing system with LRPT (Longest Remaining Processing Time) scheduling.
static Ret.qsys_prio	Qsys_mg1_prio.qsys_mg1_prio(Matrix lambda, Matrix mu, Matrix cs)	Analyzes an M/G/1 queueing system with non-preemptive (Head-of-Line) priorities.
static Ret.qsys_prio	Qsys_mg1_psjf.qsys_mg1_psjf(Matrix lambda, Matrix mu, Matrix cs)	Analyzes an M/G/1 queueing system with PSJF (Preemptive Shortest Job First) scheduling.
static Ret.qsys_prio	Qsys_mg1_setf.qsys_mg1_setf(Matrix lambda, Matrix mu, Matrix cs)	Analyzes an M/G/1 queueing system with SETF (non-preemptive FB) scheduling.
static Ret.qsys_prio	Qsys_mg1_srpt.qsys_mg1_srpt(Matrix lambda, Matrix mu, Matrix cs)	Analyzes an M/G/1 queueing system with SRPT (Shortest Remaining Processing Time) scheduling.
static QsysMapDcResult	Qsys_mapdc.qsys_phdc(Matrix alpha, Matrix T, double s, int c)	Analyzes a PH/D/c queue.
static QsysMapPhResult	Qsys_phph1.qsys_phm1(Matrix alpha, Matrix T, double mu)	Analyzes a PH/PH/1 queue with exponential service (simplified E/M/1).
static QsysMapPhResult	Qsys_mapmc.qsys_phmc(Matrix alpha, Matrix T, double mu, int c)	Analyzes a PH/M/c queue.
static QsysMapPhResult	Qsys_phph1.qsys_phph1(Matrix alpha, Matrix T, Matrix beta, Matrix S)
static QsysMapPhResult	Qsys_phph1.qsys_phph1(Matrix alpha, Matrix T, Matrix beta, Matrix S, int numQLMoms)
static QsysMapPhResult	Qsys_phph1.qsys_phph1(Matrix alpha, Matrix T, Matrix beta, Matrix S, int numQLMoms, int numQLProbs)
static QsysMapPhResult	Qsys_phph1.qsys_phph1(Matrix alpha, Matrix T, Matrix beta, Matrix S, int numQLMoms, int numQLProbs, int numSTMoms)	Analyzes a PH/PH/1 queue.

Constructors in jline.api.qsys with parameters of type Matrix

Modifier	Constructor	Description
	QsysMapDcResult(double meanQueueLength, double meanWaitingTime, double meanSojournTime, double utilization, Matrix queueLengthDist, Matrix waitingTimeDist, String analyzer)
	QsysMapPhResult(double meanQueueLength, double meanWaitingTime, double meanSojournTime, double utilization, Matrix queueLengthDist, Matrix queueLengthMoments, Matrix sojournTimeMoments, String analyzer)
	QsysRetrialResult(double L_orbit, double N_server, double L_system, double Utilization, double Throughput, double P_idle, double P_empty_orbit, double P_empty_system, Matrix pi, int truncLevel, String analyzer)

Uses of Matrix in jline.api.rl

Fields in jline.api.rl declared as Matrix

Modifier and Type	Field	Description
final Matrix	RlTdAgentGeneral.ApproximationResult.coefficients
final Matrix	RlTdAgentGeneral.ApproximationResult.X
final Matrix	RlTdAgentGeneral.HashmapResult.X
final Matrix	RlTdAgentGeneral.ApproximationResult.Y
final Matrix	RlTdAgentGeneral.HashmapResult.Y

Constructors in jline.api.rl with parameters of type Matrix

Modifier	Constructor	Description
	ApproximationResult(Matrix X, Matrix Y, Matrix coefficients)
	HashmapResult(Matrix X, Matrix Y)

Uses of Matrix in jline.api.sn

Methods in jline.api.sn that return Matrix

Modifier and Type	Method	Description
static Matrix	SnGetArvRFromTput.snGetArvRFromTput(NetworkStruct sn, Matrix TN, AvgHandle TH)	Calculates the average arrival rates at each station from the network throughputs.
static Matrix	SnGetNodeArvRFromTput.snGetNodeArvRFromTput(NetworkStruct sn, Matrix TN, AvgHandle TH, Matrix AN)
static Matrix	SnGetNodeTputFromTput.snGetNodeTputFromTput(NetworkStruct sn, Matrix TN, AvgHandle TH, Matrix ANn)
static Matrix	SnGetResidTFromRespT.snGetResidTFromRespT(NetworkStruct sn, Matrix RNclass, AvgHandle WH)	Calculates the residence times at each station from the response times.

Methods in jline.api.sn that return types with arguments of type Matrix

Modifier and Type	Method	Description
static List<Matrix>	SnFjVisitsSpn.snFjVisitsSpn(NetworkStruct sn)	Compute fork-join node visit ratios via auxiliary SPN models.
static Map<StatefulNode,Matrix>	SnGetStateAggr.snGetStateAggr(NetworkStruct sn)	Aggregates the state of the network.
static Pair<List<List<Matrix>>,Matrix>	SnRtnodesToRtorig.snRtnodesToRtorig(NetworkStruct sn)	Converts routing matrices from nodes to original format, specifically handling class switching nodes.
static Pair<List<List<Matrix>>,Matrix>	SnRtnodesToRtorig.snRtnodesToRtorig(NetworkStruct sn)	Converts routing matrices from nodes to original format, specifically handling class switching nodes.

Methods in jline.api.sn with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.snDeaggregateChainResults	SnDeaggregateChainResults.snDeaggregateChainResults(NetworkStruct sn, Matrix Lchain, Matrix ST, Matrix STchain, Matrix Vchain, Matrix alpha, Matrix Qchain, Matrix Uchain, Matrix Rchain, Matrix Tchain, Matrix Cchain, Matrix Xchain)	Calculate class-based performance metrics for a queueing network based on performance measures of its chains.
static Matrix	SnGetArvRFromTput.snGetArvRFromTput(NetworkStruct sn, Matrix TN, AvgHandle TH)	Calculates the average arrival rates at each station from the network throughputs.
static Matrix	SnGetNodeArvRFromTput.snGetNodeArvRFromTput(NetworkStruct sn, Matrix TN, AvgHandle TH, Matrix AN)
static Matrix	SnGetNodeTputFromTput.snGetNodeTputFromTput(NetworkStruct sn, Matrix TN, AvgHandle TH, Matrix ANn)
static Matrix	SnGetResidTFromRespT.snGetResidTFromRespT(NetworkStruct sn, Matrix RNclass, AvgHandle WH)	Calculates the residence times at each station from the response times.
static NetworkStruct	SnRefreshVisits.snRefreshVisits(NetworkStruct sn, Matrix chains, Matrix rt, Matrix rtnodes)
static NetworkStruct	SnSetArrival.snSetArrivalBatch(NetworkStruct sn, Matrix rates)
static NetworkStruct	SnSetArrival.snSetArrivalBatch(NetworkStruct sn, Matrix rates, Matrix scvs)
static NetworkStruct	SnSetArrival.snSetArrivalBatch(NetworkStruct sn, Matrix rates, Matrix scvs, ModifyMode mode)
static NetworkStruct	SnSetArrival.snSetArrivalBatch(NetworkStruct sn, Matrix rates, Matrix scvs, ModifyMode mode, ValidationLevel validation)
static NetworkStruct	SnSetArrival.snSetArrivalBatch(NetworkStruct sn, Matrix rates, Matrix scvs, ModifyMode mode, ValidationLevel validation, boolean autoRefresh)	Sets arrival rates for multiple classes in a single operation.
static NetworkStruct	SnSetPopulation.snSetPopulationBatch(NetworkStruct sn, Matrix njobs)
static NetworkStruct	SnSetPopulation.snSetPopulationBatch(NetworkStruct sn, Matrix njobs, ModifyMode mode)
static NetworkStruct	SnSetPopulation.snSetPopulationBatch(NetworkStruct sn, Matrix njobs, ModifyMode mode, ValidationLevel validation)
static NetworkStruct	SnSetPopulation.snSetPopulationBatch(NetworkStruct sn, Matrix njobs, ModifyMode mode, ValidationLevel validation, boolean autoRefresh)	Sets populations for multiple classes in a single operation.
static NetworkStruct	SnSetPriority.snSetPriorityBatch(NetworkStruct sn, Matrix priorities)
static NetworkStruct	SnSetPriority.snSetPriorityBatch(NetworkStruct sn, Matrix priorities, ModifyMode mode)
static NetworkStruct	SnSetPriority.snSetPriorityBatch(NetworkStruct sn, Matrix priorities, ModifyMode mode, ValidationLevel validation)	Sets priorities for multiple classes in a single operation.
static NetworkStruct	SnSetRouting.snSetRoutingMatrix(NetworkStruct sn, Matrix rt)
static NetworkStruct	SnSetRouting.snSetRoutingMatrix(NetworkStruct sn, Matrix rt, ModifyMode mode)
static NetworkStruct	SnSetRouting.snSetRoutingMatrix(NetworkStruct sn, Matrix rt, ModifyMode mode, ValidationLevel validation)
static NetworkStruct	SnSetRouting.snSetRoutingMatrix(NetworkStruct sn, Matrix rt, ModifyMode mode, ValidationLevel validation, boolean autoRefresh)	Sets the entire routing matrix for stateful nodes.
static NetworkStruct	SnSetRouting.snSetRoutingNodesMatrix(NetworkStruct sn, Matrix rtnodes)
static NetworkStruct	SnSetRouting.snSetRoutingNodesMatrix(NetworkStruct sn, Matrix rtnodes, ModifyMode mode)
static NetworkStruct	SnSetRouting.snSetRoutingNodesMatrix(NetworkStruct sn, Matrix rtnodes, ModifyMode mode, ValidationLevel validation)
static NetworkStruct	SnSetRouting.snSetRoutingNodesMatrix(NetworkStruct sn, Matrix rtnodes, ModifyMode mode, ValidationLevel validation, boolean autoRefresh)	Sets the entire routing matrix for all nodes.
static NetworkStruct	SnSetServers.snSetServersBatch(NetworkStruct sn, Matrix nServers)
static NetworkStruct	SnSetServers.snSetServersBatch(NetworkStruct sn, Matrix nServers, ModifyMode mode)
static NetworkStruct	SnSetServers.snSetServersBatch(NetworkStruct sn, Matrix nServers, ModifyMode mode, ValidationLevel validation)	Sets the number of servers for multiple stations in a single operation.
static NetworkStruct	SnSetService.snSetServiceBatch(NetworkStruct sn, Matrix rates)
static NetworkStruct	SnSetService.snSetServiceBatch(NetworkStruct sn, Matrix rates, Matrix scvs)
static NetworkStruct	SnSetService.snSetServiceBatch(NetworkStruct sn, Matrix rates, Matrix scvs, ModifyMode mode)
static NetworkStruct	SnSetService.snSetServiceBatch(NetworkStruct sn, Matrix rates, Matrix scvs, ModifyMode mode, ValidationLevel validation)
static NetworkStruct	SnSetService.snSetServiceBatch(NetworkStruct sn, Matrix rates, Matrix scvs, ModifyMode mode, ValidationLevel validation, boolean autoRefresh)	Sets service rates for multiple station-class pairs in a single operation.

Uses of Matrix in jline.api.trace

Fields in jline.api.trace declared as Matrix

Modifier and Type	Field	Description
final Matrix	Mtrace_summary.MtraceSummary.B1
final Matrix	Mtrace_summary.MtraceSummary.B2
final Matrix	Mtrace_summary.MtraceSummary.C1
final Matrix	Mtrace_summary.MtraceSummary.C2
final Matrix	Mtrace_summary.MtraceSummary.F1
final Matrix	Mtrace_summary.MtraceSummary.F2
final Matrix	Mtrace_summary.MtraceSummary.Pab
final Matrix	Mtrace_summary.MtraceSummary.Pc

Methods in jline.api.trace that return Matrix

Modifier and Type	Method	Description
static Matrix[][]	Mtrace_cov.mtrace_cov(double[] T, int[] A)	Computes the covariance matrix for multi-type traces.
static Matrix	Mtrace_cross_moment.mtrace_cross_moment(double[] T, int[] L, int k)	Computes the k-th order moment of the inter-arrival time between an event of class i and an event of class j, for all possible pairs of classes.
static Matrix	Mtrace_forward_moment.mtrace_forward_moment(double[] T, int[] A, int[] orders)
static Matrix	Mtrace_forward_moment.mtrace_forward_moment(double[] T, int[] A, int[] orders, int norm)	Computes the forward moments of a marked trace.
static Matrix	Mtrace_iat2counts.mtrace_iat2counts(double[] T, int[] A, double scale)	Computes the per-class counting processes of T, i.e., the counts after "scale" units of time from an arrival.
static Matrix	Mtrace_joint.mtrace_joint(double[] T, int[] A, int[] i)	Given a multi-class trace, computes the empirical class-dependent joint moments that estimate E[ ( X^(a)_j )^i(1) (X^(a)_(j+l) )^i(2) ] for all classes a.
static Matrix	Mtrace_mean.mtrace_mean(double[] trace, int ntypes, int[] type)	Computes the mean of a trace, divided by types.
static Matrix	Mtrace_moment.mtrace_moment(double[] T, int[] A, int[] orders)
static Matrix	Mtrace_moment.mtrace_moment(double[] T, int[] A, int[] orders, int after)
static Matrix	Mtrace_moment.mtrace_moment(double[] T, int[] A, int[] orders, int after, int norm)	Computes the empirical class-dependent moments of a multi-class trace.
static Matrix	Mtrace_moment_simple.mtrace_moment_simple(double[] T, int[] L, int k)	Computes the k-th order moment of the inter-arrival time between an event of class i and an event of class j, for all possible pairs of classes.
static Matrix	Mtrace_pc.mtrace_pc(double[] T, int[] C)	Computes the probabilities of arrival for each class.
static Matrix	Mtrace_sigma.mtrace_sigma(double[] T, int[] L)	Computes the empirical probability of observing a specific 2-element sequence of events, i.e.

Constructors in jline.api.trace with parameters of type Matrix

Modifier	Constructor	Description
	MtraceSummary(double[] M, double[] ACF, Matrix F1, Matrix F2, Matrix B1, Matrix B2, Matrix C1, Matrix C2, Matrix Pc, Matrix Pab)

Uses of Matrix in jline.api.wf

Fields in jline.api.wf declared as Matrix

Modifier and Type	Field	Description
final Matrix	Wf_analyzer.WorkflowRepresentation.linkMatrix

Methods in jline.api.wf that return Matrix

Modifier and Type	Method	Description
Matrix	Wf_pattern_updater.ServiceParameters.getAlpha()
Matrix	Wf_analyzer.WorkflowRepresentation.getLinkMatrix()
Matrix	Wf_pattern_updater.UpdatedWorkflow.getLinkMatrix()
Matrix	Wf_pattern_updater.ServiceParameters.getT()

Methods in jline.api.wf with parameters of type Matrix

Modifier and Type	Method	Description
static List<Wf_branch_detector.BranchPattern>	Wf_branch_detector.detectBranches(Matrix linkMatrix, List<Integer> serviceNodes, List<Integer> joinNodes)
static List<Integer>	Wf_loop_detector.detectLoops(Matrix linkMatrix, List<Integer> serviceNodes, List<Integer> routerNodes)
static List<Integer>	Wf_loop_detector.detectLoops(Matrix linkMatrix, List<Integer> serviceNodes, List<Integer> routerNodes, List<Integer> joinNodes)
static List<List<Integer>>	Wf_parallel_detector.detectParallel(Matrix linkMatrix, List<Integer> serviceNodes, List<Integer> forkNodes, List<Integer> joinNodes)	Detect parallel patterns in a workflow network.
static List<List<Integer>>	Wf_sequence_detector.detectSequences(Matrix linkMatrix, List<Integer> serviceNodes)	Detect sequence patterns in a workflow network.
static double	Wf_loop_detector.getLoopProbability(int serviceNode, Matrix linkMatrix, List<Integer> routerNodes)
static Map<String,Object>	Wf_loop_detector.getLoopStats(List<Integer> loopNodes, Matrix linkMatrix, List<Integer> routerNodes)
static Map<String,Object>	Wf_pattern_updater.getUpdateStats(Matrix originalMatrix, Wf_pattern_updater.UpdatedWorkflow updatedWorkflow)
static Wf_pattern_updater.UpdatedWorkflow	Wf_pattern_updater.updatePatterns(Matrix linkMatrix, List<Integer> serviceNodes, List<Integer> forkNodes, List<Integer> joinNodes, List<Integer> routerNodes, Map<Integer,Wf_pattern_updater.ServiceParameters> serviceParams)
static boolean	Wf_branch_detector.validateBranchPattern(Wf_branch_detector.BranchPattern pattern, Matrix linkMatrix)
static boolean	Wf_loop_detector.validateLoopPattern(int loopNode, Matrix linkMatrix, List<Integer> routerNodes)
static boolean	Wf_parallel_detector.validateParallelPattern(List<Integer> pattern, Matrix linkMatrix, List<Integer> forkNodes, List<Integer> joinNodes)
static boolean	Wf_sequence_detector.validateSequence(List<Integer> sequence, Matrix linkMatrix)	Validate that a sequence chain is properly connected.

Constructors in jline.api.wf with parameters of type Matrix

Modifier	Constructor	Description
	ServiceParameters(Matrix alpha, Matrix T)
	UpdatedWorkflow(Matrix linkMatrix, Map<Integer,Wf_pattern_updater.ServiceParameters> serviceParameters)
	WorkflowRepresentation(Matrix linkMatrix, List<Integer> serviceNodes, List<Integer> forkNodes, List<Integer> joinNodes, List<Integer> routerNodes, Map<Integer,Wf_pattern_updater.ServiceParameters> serviceParameters)

Uses of Matrix in jline.bench

Methods in jline.bench that return Matrix

Modifier and Type	Method	Description
static Matrix	BenchmarkUtils.randGallery(int rows, int cols, int seed)	Generate random gallery matrix (similar to MATLAB's randgallery) This creates a random matrix with values in [0,1]

Methods in jline.bench with parameters of type Matrix

Modifier and Type	Method	Description
static double	BenchmarkUtils.errOnSum(Matrix approx, Matrix exact)	Calculate mean error on sum for queue length metrics Returns mean absolute error relative to sum of each column Similar to MATLAB: mean(abs(exact-approx))/sum(exact)
static double	BenchmarkUtils.mape(Matrix approx, Matrix exact)	Calculate Mean Absolute Percentage Error (MAPE) Wrapper for Utils.mape for benchmark compatibility
static double	BenchmarkUtils.maxErrorOnSum(Matrix approx, Matrix exact)	Calculate maximum error on sum for queue length metrics Returns max absolute error relative to sum of each column Similar to MATLAB: max(abs(exact-approx))/sum(exact)
static double	BenchmarkUtils.utilizationError(Matrix approx, Matrix exact, Network model)	Calculate utilization error for benchmarks Excludes delay stations (row 0) from comparison

Uses of Matrix in jline.examples

Methods in jline.examples that return Matrix

Modifier and Type	Method	Description
static Matrix	NetworkGeneratorExample.starTopology(int n)	Custom topology function - creates a star topology where node 0 is connected to all other nodes

Uses of Matrix in jline.gen

Methods in jline.gen that return Matrix

Modifier and Type	Method	Description
static Matrix	NetworkGenerator.cyclicGraph(int numVertices)	Generate a cyclic graph topology
static Matrix	NetworkGenerator.randGraph(int numVertices)	Generate a random strongly connected graph topology This implements the algorithm from MATLAB's randGraph function

Method parameters in jline.gen with type arguments of type Matrix

Modifier and Type	Method	Description
void	NetworkGenerator.setTopologyFcn(Function<Integer,Matrix> fcn)

Constructor parameters in jline.gen with type arguments of type Matrix

Modifier	Constructor	Description
	NetworkGenerator(String schedStrat, String routingStrat, String distribution, String cclassJobLoad, boolean hasVaryingServiceRates, boolean hasMultiServerQueues, boolean hasRandomCSNodes, boolean hasMultiChainCS, boolean initializeStates, Function<Integer,Matrix> topologyFcn)	Constructor with all options including state initialization
	NetworkGenerator(String schedStrat, String routingStrat, String distribution, String cclassJobLoad, boolean hasVaryingServiceRates, boolean hasMultiServerQueues, boolean hasRandomCSNodes, boolean hasMultiChainCS, Function<Integer,Matrix> topologyFcn)	Constructor with custom settings

Uses of Matrix in jline.inference.api

Fields in jline.inference.api declared as Matrix

Modifier and Type	Field	Description
final Matrix	Infer_fluid_ps_rt_likelihood.FluidPsRtResult.augPhases
final Matrix	Infer_fluid_ps_rt_likelihood.FluidPsRtResult.qIndices

Methods in jline.inference.api that return Matrix

Modifier and Type	Method	Description
static Matrix	Infer_compute_ql_at_arrival.infer_compute_ql_at_arrival(double[] at, int[] atJobid, double[] rt, int[] rtJobid, int[] classVec, int R)	Compute per-class queue lengths at arrival.
static Matrix	Infer_qmle.infer_qmle(Matrix Q, double[] N, double[] Z)	Quick Maximum Likelihood Estimation closed-form formula.

Methods in jline.inference.api that return types with arguments of type Matrix

Modifier and Type	Method	Description
static List<Matrix>	Infer_get_qlen_arrival.infer_get_qlen_arrival(double[][][] data, int K)	Compute queue lengths at arrival from legacy cell data format.

Methods in jline.inference.api with parameters of type Matrix

Modifier and Type	Method	Description
static double	Infer_fluid_ps_rt_likelihood.infer_fluid_ps_rt_solve(Infer_fluid_ps_rt_likelihood.FluidPsRtResult result, Matrix y0Levels, double Rsampled, int taggedClass)
static double[]	Infer_fmlps.infer_fmlps(Network model, Queue node, double[] rt, int[] classVec, Matrix ql, int W)	FMLPS demand estimation using fluid-based likelihood.
static double[]	Infer_minps.infer_minps(Network model, Queue node, double[] rt, int[] classVec, Matrix ql)	MINPS demand estimation method.
static double[]	Infer_mlps.infer_mlps(Network model, Queue node, double[] rt, int[] classVec, Matrix ql)
static Matrix	Infer_qmle.infer_qmle(Matrix Q, double[] N, double[] Z)	Quick Maximum Likelihood Estimation closed-form formula.
static double[]	Infer_rps.infer_rps(double[] rt, int[] classVec, Matrix ql, int V)	Regression for Processor Sharing (RPS) demand estimation.

Constructors in jline.inference.api with parameters of type Matrix

Modifier	Constructor	Description
	FluidPsRtResult(org.apache.commons.math3.ode.FirstOrderDifferentialEquations ode, Matrix qIndices, Matrix augPhases, int stateSize, int refIdx, int newK)

Uses of Matrix in jline.inference.lang

Methods in jline.inference.lang that return Matrix

Modifier and Type	Method	Description
Matrix	ParamEstimator.estimateAt(List<Station> nodes)

Uses of Matrix in jline.inference.util

Methods in jline.inference.util that return Matrix

Modifier and Type	Method	Description
static Matrix	NnlsSolver.lsqnonneg(Matrix A, Matrix b)	Solve the NNLS problem: min ||Ax - b||^2 subject to x >= 0.

Methods in jline.inference.util that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Double>	OptimUtils.quadprog(Matrix H, Matrix f, Matrix lb)	Quadratic program solver with non-negative constraints.

Methods in jline.inference.util with parameters of type Matrix

Modifier and Type	Method	Description
static Matrix	NnlsSolver.lsqnonneg(Matrix A, Matrix b)	Solve the NNLS problem: min ||Ax - b||^2 subject to x >= 0.
static Pair<Matrix,Double>	OptimUtils.quadprog(Matrix H, Matrix f, Matrix lb)	Quadratic program solver with non-negative constraints.

Uses of Matrix in jline.io

Fields in jline.io declared as Matrix

Modifier and Type	Field	Description
Matrix	Ret.snGetDemands.alpha
Matrix	Ret.snToAG.AP
Matrix	Ret.pfqnProcomom2.B
Matrix	Ret.lossnErlangFP.blockProb
Matrix	Ret.pfqnFnc.c
Matrix	Ret.pfqnAMVA.C
Matrix	Ret.pfqnAMVAMS.C
Matrix	Ret.pfqnAMVASchmidt.C	Waiting time matrix (M x R)
Matrix	Ret.snDeaggregateChainResults.C
Matrix	Ret.pfqnAB.CN	Waiting time matrix (M x R)
Matrix	Ret.pfqnSchmidt.CN	Waiting time matrix (M x R)
final Matrix	Ret.pfqnLeFpi.d
final Matrix	Ret.pfqnLeFpiZ.d
Matrix	Ret.snGetDemands.D
Matrix	Ret.snGetProductFormParams.D
Matrix	Ret.snGetDemands.Dchain
Matrix	Ret.pfqnMVALDMXEC.E
Matrix	Ret.pfqnMVALDMXEC.EC
Matrix	Ret.pfqnMVALDMXEC.Eprime
Matrix	Ret.npfqnNonexpApprox.eta
Matrix	Ret.SampleResult.event	Event sequence corresponding to the state trajectory.
Matrix	Ret.pfqnProcomom2.F
Matrix	Ret.FJApprox.fjclassmap
Matrix	Ret.FJApprox.fjforkmap
Matrix	Ret.cacheGamma.gamma
Matrix	Ret.npfqnNonexpApprox.gamma
Matrix	Ret.getHashOrAddResult.hashid
Matrix	Ret.pfqnNcSanitize.L
Matrix	Ret.pfqnNcSanitize.lambda
Matrix	Ret.snGetProductFormParams.lambda
Matrix	Ret.pfqnComomrm.lGbasis
Matrix	Ret.pfqnMVALDMXEC.Lo
Matrix	Ret.lossnErlangFP.lossProb
Matrix	Ret.pfqnFnc.mu
Matrix	Ret.snGetProductFormParams.mu
Matrix	Ret.pfqnNcSanitize.N
Matrix	Ret.snGetProductFormParams.N
Matrix	Ret.snGetDemands.Nchain
Matrix	Ret.npfqnNonexpApprox.nservers
Matrix	Ret.FJsortForks.outerForks
Matrix	Ret.afterEventHashedOrAddResult.outhash
Matrix	Ret.afterEventHashedOrAddResult.outprob
final Matrix	Ret.EventResult.outprob
Matrix	Ret.afterEventHashedOrAddResult.outrate
final Matrix	Ret.EventResult.outrate
final Matrix	Ret.EventResult.outspace
Matrix	Ret.LinearizerResult.P
Matrix[]	Ret.pfqnLinearizerMSEstimate.P_1
Matrix	Ret.FJsortForks.parentForks
Matrix	Ret.LinearizerResult.PB
final Matrix	Ret.pfqnEstimate.PB_1
Matrix	Ret.pfqnLinearizerMSEstimate.PB_1
Matrix	Ret.pfqnMVALDMX.Pc
Matrix	Ret.cacheMVA.pi
Matrix	Ret.pfqnMVALD.pi
Matrix	Ret.cacheMVA.pi0
Matrix	Ret.cacheXiFp.pi0
Matrix	Ret.cacheMVA.pij
Matrix	Ret.cacheXiFp.pij
Matrix	Ret.pfqnProcomom2.pk
Matrix	Ret.pfqnProcomom.Pr
Matrix	Ret.pfqnComomrmLd.prob
Matrix	Ret.pfqnComomrmMs.prob
Matrix	Ret.ProbabilityResult.probability	The probability value(s).
Matrix	Ret.snToAG.processMap
Matrix	Ret.LinearizerResult.Q
Matrix	Ret.pfqnAMVA.Q
Matrix	Ret.pfqnAMVAMS.Q
Matrix	Ret.pfqnAMVASchmidt.Q	Queue length matrix (M x R)
Matrix	Ret.pfqnMom.Q
Matrix	Ret.pfqnMVA.Q
Matrix	Ret.pfqnMVALD.Q
Matrix	Ret.pfqnMVALDMX.Q
Matrix	Ret.pfqnNcXQ.Q
Matrix	Ret.pfqnProcomom.Q
Matrix	Ret.pfqnQd.Q
Matrix	Ret.snDeaggregateChainResults.Q
Matrix[]	Ret.pfqnLinearizerEstimate.Q_1
Matrix[]	Ret.pfqnLinearizerMSEstimate.Q_1
Matrix	Ret.lossnErlangFP.qLen
Matrix	Ret.pfqnAB.QN	Queue length matrix (M x R)
Matrix	Ret.pfqnSchmidt.QN	Queue length matrix (M x R)
Matrix	Ret.pfqnAMVA.R
Matrix	Ret.pfqnAMVAMS.R
Matrix	Ret.pfqnMVA.R
Matrix	Ret.pfqnMVALD.R
Matrix	Ret.pfqnMVALDMX.R
Matrix	Ret.snDeaggregateChainResults.R
Matrix[][]	Ret.snToAG.R
Matrix	Ret.snGetDemands.refstatchain
Matrix	Ret.npfqnNonexpApprox.rho
Matrix	Ret.pfqnAB.RN	Response time matrix (M x R)
Matrix	Ret.pfqnSchmidt.RN	Response time matrix (M x R)
Matrix	Ret.SVD.s
Matrix	Ret.snGetProductFormParams.S
Matrix	Ret.npfqnNonexpApprox.scva
Matrix	Ret.snGetDemands.SCVchain
Matrix	Ret.npfqnNonexpApprox.scvs
Matrix	Ret.SpectralDecomposition.spectrum
Matrix	Ret.reachableSpaceGeneratorResult.SSh
Matrix	Ret.reachableSpaceGeneratorResult.SSq
Matrix	Ret.npfqnNonexpApprox.ST
Matrix	Ret.ProbabilityResult.state	The state specification for which the probability was computed.
Matrix	Ret.snGetDemands.STchain
Matrix	Ret.SampleResult.t	Time points for the sampled trajectory.
Matrix	Ret.LinearizerResult.T
Matrix	Ret.pfqnAMVA.T
Matrix	Ret.snDeaggregateChainResults.T
final Matrix	Ret.pfqnEstimate.T_1
Matrix	Ret.pfqnLinearizerEstimate.T_1
Matrix	Ret.DistributionResult.timePoints	Time points for transient distributions.
Matrix	Ret.pfqnAB.TN	Throughput matrix (M x R)
Matrix	Ret.pfqnSchmidt.TN	Throughput matrix (M x R)
Matrix	Ret.cacheMVA.u
final Matrix	Ret.pfqnLeFpi.u
final Matrix	Ret.pfqnLeFpiZ.u
Matrix	Ret.SVD.u
Matrix	Ret.pfqnAMVA.U
Matrix	Ret.pfqnAMVAMS.U
Matrix	Ret.pfqnAMVASchmidt.U	Utilization matrix (M x R)
Matrix	Ret.pfqnMVA.U
Matrix	Ret.pfqnMVALD.U
Matrix	Ret.pfqnMVALDMX.U
Matrix	Ret.pfqnQd.U
Matrix	Ret.snDeaggregateChainResults.U
Matrix	Ret.pfqnAB.UN	Utilization matrix (M x R)
Matrix	Ret.pfqnSchmidt.UN	Utilization matrix (M x R)
Matrix	Ret.SVD.v
Matrix	Ret.snGetProductFormParams.V
Matrix	Ret.Eigs.values
Matrix	Ret.snGetDemands.Vchain
Matrix	Ret.Eigs.vectors
Matrix	Ret.LinearizerResult.W
static Matrix	Ret.qsys_prio.W
Matrix	Ret.cacheMVA.x
Matrix	Ret.LinearizerResult.X
Matrix	Ret.pfqnAMVA.X
Matrix	Ret.pfqnAMVAMS.X
Matrix	Ret.pfqnAMVASchmidt.X	System throughput vector (1 x R)
Matrix	Ret.pfqnMom.X
Matrix	Ret.pfqnMVA.X
Matrix	Ret.pfqnMVALD.X
Matrix	Ret.pfqnMVALDMX.X
Matrix	Ret.pfqnNcXQ.X
Matrix	Ret.pfqnQd.X
Matrix	Ret.snDeaggregateChainResults.X
Matrix	Ret.cacheSpm.xi
Matrix	Ret.cacheXiFp.xi
Matrix	Ret.pfqnAB.XN	System throughput vector (1 x R)
Matrix	Ret.pfqnSchmidt.XN	System throughput vector (1 x R)
Matrix	Ret.pfqnNcSanitize.Z
Matrix	Ret.snGetDemands.Z
Matrix	Ret.snGetProductFormParams.Z

Fields in jline.io with type parameters of type Matrix

Modifier and Type	Field	Description
List<List<Matrix>>	Ret.DistributionResult.cdfData	The CDF data organized as a cell array [stations x classes].
List<Matrix>	Ret.pfqnSchmidt.PN	State probabilities per station
List<Matrix>	Ret.pfqnProcomom2.T

Methods in jline.io that return Matrix

Modifier and Type	Method	Description
Matrix	Ret.DistributionResult.getCdf(int station, int jobClass)	Gets the CDF for a specific station and class.
Matrix	Ret.ProbabilityResult.getProbabilityMatrix()	Gets the probability matrix.
Matrix	Ret.SampleResult.getStateMatrix()	Gets the state trajectory as a matrix (for single-node sampling).

Methods in jline.io that return types with arguments of type Matrix

Modifier and Type	Method	Description
List<List<Matrix>>	Ret.DistributionResult.getAllCdfData()	Gets the complete CDF data structure.
List<Matrix>	Ret.SampleResult.getSystemStateList()	Gets the system state trajectories as a list of matrices (for system-wide sampling).

Methods in jline.io with parameters of type Matrix

Modifier and Type	Method	Description
void	Ret.DistributionResult.setCdf(int station, int jobClass, Matrix cdf)	Sets the CDF for a specific station and class.
static Ret.LinearizerResult	Ret.LinearizerResult.withX(Matrix Q, Matrix W, Matrix X, Matrix P, Matrix PB, int iter)

Constructors in jline.io with parameters of type Matrix

Modifier	Constructor	Description
	afterEventHashedOrAddResult(Matrix outhash, Matrix outrate, Matrix outprob, NetworkStruct sn)
	cacheGamma(Matrix gamma, int u, int n, int h)	Constructor for initializing the cacheGammaLpReturn object.
	cacheMVA(Matrix pi, Matrix pi0, Matrix pij, Matrix x, Matrix u, int E)	Constructor for initializing the cacheMVAReturn object.
	cacheRayInt(double Z, double lZ, Matrix xi)	Deprecated.
	cacheSpm(double Z, double lZ, Matrix xi)	Constructor for initializing the cacheSpmReturn object.
	cacheXiFp(Matrix xi, Matrix pi0, Matrix pij, int it)	Creates a new cacheXiFp result object.
	DistributionResult(int numStations, int numClasses, String distributionType, Matrix timePoints)	Constructor for transient distributions.
	Eigs(Matrix s, Matrix V)
	EventResult(Matrix outspace, Matrix outrate, Matrix outprob)
	FJApprox(Network nonfjmodel, Matrix fjclassmap, Matrix fjforkmap, Map<Integer,Integer> fj_auxiliary_delays, Map<Integer,Integer> fanout)
	FJsortForks(Matrix outerForks, Matrix parentForks)
	getHashOrAddResult(Matrix hashid, NetworkStruct sn)
	LinearizerResult(Matrix Q, Matrix W, Matrix T)
	LinearizerResult(Matrix Q, Matrix W, Matrix T, int iter)
	LinearizerResult(Matrix Q, Matrix W, Matrix T, Matrix P, Matrix PB)
	LinearizerResult(Matrix Q, Matrix W, Matrix T, Matrix P, Matrix PB, int iter)
	LinearizerResult(Matrix Q, Matrix W, Matrix T, Matrix X, Matrix P, Matrix PB, Integer iter)
	lossnErlangFP(Matrix q, Matrix l, Matrix b, int n)
	npfqnNonexpApprox(Matrix ST, Matrix gamma, Matrix nservers, Matrix rho, Matrix scva, Matrix scvs, Matrix eta)
	pfqnAB(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, String method, int iter, double runtime)
	pfqnAMVA(Matrix Q, Matrix U, Matrix R, Matrix T, Matrix C, Matrix X, int totiter)
	pfqnAMVAMS(Matrix Q, Matrix U, Matrix R, Matrix C, Matrix X, int totiter)
	pfqnAMVASchmidt(Matrix XN, Matrix QN, Matrix UN, Matrix CN, List<Map<Object,Double>> PN)
	pfqnComomrm(double lG, Matrix lGbasis)
	pfqnComomrmLd(double GN, double lG, Matrix prob)
	pfqnComomrmMs(double G, double lG, Matrix prob)
	pfqnCUB(Matrix L, double Nt, Matrix beta)
	pfqnEstimate(MatrixCell Q_1, MatrixCell P_1, Matrix PB_1, Matrix T_1)
	pfqnFnc(Matrix mu, Matrix c)
	pfqnLeFpi(Matrix u, Matrix d)
	pfqnLeFpiZ(Matrix u, double v, Matrix d)
	pfqnLinearizerEstimate(Matrix[] Q_1, Matrix T_1)
	pfqnLinearizerMSEstimate(Matrix[] Q_1, Matrix[] P_1, Matrix PB_1)
	pfqnMom(Matrix X, Matrix Q, org.apache.commons.math3.fraction.BigFraction G, double lG, org.apache.commons.math3.fraction.BigFraction[] g, org.apache.commons.math3.fraction.BigFraction[] g_1)
	pfqnMVA(Matrix XN, Matrix QN, Matrix UN, Matrix RN, double lGN)
	pfqnMVALD(Matrix XN, Matrix QN, Matrix UN, Matrix RN, List<Double> lG, boolean isNumStable, Matrix pi)
	pfqnMVALDMX(Matrix XN, Matrix QN, Matrix UN, Matrix RN, double lG, Matrix Pc)
	pfqnMVALDMXEC(Matrix EC, Matrix E, Matrix Eprime, Matrix Lo)
	pfqnNcSanitize(Matrix lambda, Matrix L, Matrix N, Matrix Z, double lGremaind)
	pfqnNcXQ(Double G, Double lG, Matrix X, Matrix Q, String method)
	pfqnNcXQ(Double lG, Matrix X, Matrix Q, String method)
	pfqnProcomom(Matrix Pr, Matrix Q)
	pfqnProcomom2(Matrix pk, double lG, double G, List<Matrix> T, Matrix F, Matrix B)
	pfqnQd(Matrix Q, Matrix X, Matrix U, int iter)
	pfqnSchmidt(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, List<Matrix> PN, String method, int iter, double runtime)
	ProbabilityResult(Matrix probability)	Constructor for matrix probability results.
	qsys_prio(Matrix W, double rho)	Constructs a qsys_prio return object.
	reachableSpaceGeneratorResult(Matrix SSq, Matrix SSh, NetworkStruct sn)
	SampleResult(String handle, Matrix t, List<Matrix> systemState, Matrix event, boolean isAggregate, int numEvents)	Constructor for system-wide sampling results.
	SampleResult(String handle, Matrix t, Matrix state, Matrix event, boolean isAggregate, Integer nodeIndex, int numEvents)	Constructor for single-node sampling results.
	snDeaggregateChainResults(Matrix q, Matrix u, Matrix r, Matrix t, Matrix c, Matrix x)
	snGetDemands(Matrix D, Matrix Z)
	snGetDemands(Matrix Dchain, Matrix STchain, Matrix Vchain, Matrix alpha, Matrix Nchain, Matrix SCVchain, Matrix refstatchain)
	snGetDemands(Matrix D, Matrix Z, Matrix Dchain, Matrix STchain, Matrix Vchain, Matrix alpha, Matrix Nchain, Matrix SCVchain, Matrix refstatchain)
	snToAG(Matrix[][] R, Matrix AP, Matrix processMap, List<Ret.ActionMapEntry> actionMap, int[] N)
	SpectralDecomposition(Matrix s, MatrixCell p)
	SVD(Matrix u, Matrix s, Matrix v)

Constructor parameters in jline.io with type arguments of type Matrix

Modifier	Constructor	Description
	pfqnProcomom2(Matrix pk, double lG, double G, List<Matrix> T, Matrix F, Matrix B)
	pfqnSchmidt(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, List<Matrix> PN, String method, int iter, double runtime)
	SampleResult(String handle, Matrix t, List<Matrix> systemState, Matrix event, boolean isAggregate, int numEvents)	Constructor for system-wide sampling results.

Uses of Matrix in jline.io.tikz

Fields in jline.io.tikz declared as Matrix

Modifier and Type	Field	Description
Matrix	SequenceDiagramTraverser.Fragment.params

Uses of Matrix in jline.lang

Fields in jline.lang declared as Matrix

Modifier and Type	Field	Description
Matrix	ModelAdapter.DeaggInfo.alpha
Matrix	NetworkStruct.cap
Matrix	Network.routingMatrixReturn.chains
Matrix	NetworkStruct.chains
Matrix	NetworkStruct.classcap
Matrix	NetworkStruct.classdeadline
Matrix	NetworkStruct.classprio
protected Matrix	Chain.completes
Matrix	NetworkStruct.connmatrix
Matrix	NetworkStruct.csmask
Matrix	NetworkStruct.fj
Matrix	NetworkStruct.immfeed
Matrix	NetworkStruct.isCatastrophe
Matrix	NetworkStruct.issignal
Matrix	NetworkStruct.isslc
Matrix	NetworkStruct.isstatedep
Matrix	NetworkStruct.isstateful
Matrix	NetworkStruct.isstation
Matrix	ModelAdapter.DeaggInfo.lambdaChain
Matrix	ModelAdapter.DeaggInfo.Lchain
Matrix	Network.routingMatrixReturn.linksmat
Matrix	NetworkStruct.lldscaling
Matrix	ModelAdapter.DeaggInfo.Nchain
protected Matrix	Chain.njobs
Matrix	NetworkStruct.njobs
Matrix	NetworkStruct.nodeToStateful
Matrix	NetworkStruct.nodeToStation
Matrix	NetworkStruct.nservers
Matrix	NetworkStruct.nservertypes	Number of server types per station.
Matrix	NetworkStruct.nvars
Matrix	NetworkStruct.phases
Matrix	NetworkStruct.phaseshift
Matrix	NetworkStruct.phasessz
Matrix	Environment.probEnv
Matrix	Environment.probOrig
Matrix	NetworkStruct.rates
Matrix	NetworkStruct.refclass
Matrix	ModelAdapter.DeaggInfo.refstat
Matrix	NetworkStruct.refstat
Matrix	ModelAdapter.DeaggInfo.refstatchain
Matrix	NetworkStruct.regionrule
Matrix	NetworkStruct.regionsz
Matrix	NetworkStruct.regionweight
Matrix	Network.routingMatrixReturn.rt
Matrix	NetworkStruct.rt
Matrix	Network.routingMatrixReturn.rtnodes
Matrix	NetworkStruct.rtnodes
Matrix	NetworkStruct.schedparam
Matrix	NetworkStruct.scv
Matrix	ModelAdapter.DeaggInfo.SCVchain
protected Matrix	Event.state
Matrix	ModeEvent.state
Matrix	NetworkStruct.statefulToNode
Matrix	NetworkStruct.statefulToStation
Matrix	NetworkStruct.stationToNode
Matrix	NetworkStruct.stationToStateful
Matrix	ModelAdapter.DeaggInfo.STchain
Matrix	NetworkStruct.syncreply
Matrix	NetworkStruct.varsparam
Matrix	ModelAdapter.DeaggInfo.Vchain
protected Matrix	Chain.visits

Fields in jline.lang with type parameters of type Matrix

Modifier and Type	Field	Description
Map<Station,SerializableFunction<Matrix,Double>>	NetworkStruct.cdscaling
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.impatienceMu
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.impatiencePhi
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.impatiencePie
Map<Integer,Matrix>	ModelAdapter.DeaggInfo.inchain
Map<Integer,Matrix>	NetworkStruct.inchain
Map<Station,Matrix>	NetworkStruct.ljcdcutoffs
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.ljcdscaling
Map<Station,Matrix>	NetworkStruct.ljdcutoffs
Map<Station,Matrix>	NetworkStruct.ljdscaling
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.mu
Map<Integer,Matrix>	NetworkStruct.nodevisits
Map<JobClass,Matrix>	NodeParam.outlinks	Outbound link specifications by job class - defines outgoing connections
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.phi
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.pie
protected SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double>	Event.probFun
protected SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double>	Event.probFun
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.retrialMu
Map<Station,Map<JobClass,Matrix>>	NetworkStruct.retrialPhi
Map<JobClass,Matrix>	NodeParam.rlValueFunction	RL value function by job class.
Map<JobClass,Map<JobClass,Matrix>>	Network.routingMatrixReturn.rtNodesByClass
Map<Node,Map<Node,Matrix>>	Network.routingMatrixReturn.rtNodesByStation
Map<JobClass,Map<JobClass,Matrix>>	NetworkStruct.rtorig
Map<Station,Matrix>	NetworkStruct.servercompat	Server-class compatibility matrix per station.
Map<Station,Matrix>	NetworkStruct.serverspertype	Number of servers per server type at each station.
Map<StatefulNode,Matrix>	NetworkStruct.space
Map<StatefulNode,Matrix>	NetworkStruct.state
Map<StatefulNode,Matrix>	NetworkStruct.stateprior
Map<Integer,Matrix>	NetworkStruct.visits
Map<JobClass,Matrix>	NodeParam.weights	Routing weights by job class - controls probabilistic routing decisions
Map<JobClass,Matrix>	NodeParam.withMemory	Memory-dependent parameters by job class - for state-dependent behavior

Methods in jline.lang that return Matrix

Modifier and Type	Method	Description
static Matrix	ModelAdapter.findPaths(NetworkStruct sn, Matrix P, int startNode, int endNode, int r, ArrayList<Integer> toMerge, Matrix QN, Matrix TN, double currentTime, Matrix fjclassmap, Matrix fjforkmap, Network nonfjmodel)	Finds the response times along each path leading out of startNode up to (and not including) endNode
static Matrix	ModelAdapter.findPathsCS(NetworkStruct sn, Matrix P, int curNode, int endNode, int curClass, ArrayList<Integer> toMerge, Matrix QN, Matrix TN, double currentTime, Matrix fjclassmap, Matrix fjforkmap, Network nonfjmodel)	Finds the response times along each path leading out of curNode up to (and not including) endNode Variant for models with class switching
Matrix	RoutingMatrix.get(int jobclass1, int jobclass2)
Matrix	RoutingMatrix.get(JobClass jobclass1, JobClass jobclass2)
Matrix	ModelAdapter.AggregateChainResult.getAlpha()
Matrix	Network.getClassSwitchingMask()
Matrix	Network.getConnectionMatrix()
Matrix	Region.getConstraintA()	Gets the linear constraint matrix A.
Matrix	Region.getConstraintB()	Gets the linear constraint vector b.
Matrix	Network.getCsMatrix()
Matrix	Network.getDemandsChain()
Matrix	Network.getForkJoins()
Matrix	Network.getLimitedLoadDependence()
Matrix	ClassSwitchMatrix.getMatrix()	Expose the raw Matrix only if callers genuinely need it
Matrix	Network.getNumberOfJobs()
Matrix	Network.getReferenceClasses()
Matrix	Network.getReferenceStations()
Matrix	Event.getState()	Gets the system state matrix when this event occurred.
Matrix	ModeEvent.getState()
Matrix	Network.getStatefulServers()
Matrix	Network.getStationServers()
Matrix	Environment.ResetQueueLengthsFunction.reset(Matrix input)

Methods in jline.lang that return types with arguments of type Matrix

Modifier and Type	Method	Description
Map<Station,SerializableFunction<Matrix,Double>>	Network.getLimitedClassDependence()
Pair<Map<Station,Map<JobClass,Matrix>>,Map<Station,Matrix>>	Network.getLimitedJointClassDependence()	Gets the limited joint-class-dependent scaling tables and cutoffs for all stations.
Pair<Map<Station,Map<JobClass,Matrix>>,Map<Station,Matrix>>	Network.getLimitedJointClassDependence()	Gets the limited joint-class-dependent scaling tables and cutoffs for all stations.
Pair<Map<Station,Matrix>,Map<Station,Matrix>>	Network.getLimitedJointDependence()	Gets the limited joint-dependent scaling tables and cutoffs for all stations.
Pair<Map<Station,Matrix>,Map<Station,Matrix>>	Network.getLimitedJointDependence()	Gets the limited joint-dependent scaling tables and cutoffs for all stations.
Map<JobClass,Map<JobClass,Matrix>>	Network.getLinkedRoutingMatrix()
SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double>	Event.getProbFun()	Gets the probability function used to dynamically compute event probability.
SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double>	Event.getProbFun()	Gets the probability function used to dynamically compute event probability.

Methods in jline.lang with parameters of type Matrix

Modifier and Type	Method	Description
static Network	Network.cluster(Matrix lambda, Matrix D, SchedStrategy[] strategy, Matrix S, RoutingStrategy dispatching)	Creates an open cluster network: Source -> Dispatcher (Router) -> Servers -> Sink.
static Network	Network.clusterClosed(Matrix N, Matrix Z, Matrix D, SchedStrategy[] strategy, Matrix S, RoutingStrategy dispatching)	Creates a closed cluster network: Think (Delay) -> Dispatcher (Router) -> Servers -> Think.
static Network	Network.clusterFcfs(Matrix lambda, Matrix D, Matrix S, RoutingStrategy dispatching)	Creates an open FCFS cluster with one server per queue.
static Network	Network.clusterPs(Matrix lambda, Matrix D, RoutingStrategy dispatching)	Creates an open PS cluster with one server per queue.
static Network	Network.clusterPs(Matrix lambda, Matrix D, Matrix S, RoutingStrategy dispatching)	Creates an open PS cluster.
static Network	Network.cyclic(Matrix N, Matrix D, SchedStrategy[] strategy, Matrix S)	Creates a cyclic queueing network model with specified job populations, service demands, scheduling strategies, and server counts.
static Network	Network.cyclicFcfs(Matrix N, Matrix D)	Creates a cyclic queueing network with First Come First Served (FCFS) scheduling at all stations.
static Network	Network.cyclicFcfs(Matrix N, Matrix D, Matrix S)	Creates a cyclic queueing network with FCFS scheduling and specified server counts.
static Network	Network.cyclicFcfsInf(Matrix N, Matrix D, Matrix Z)	Creates a cyclic network with infinite server (delay) stations followed by FCFS queue stations.
static Network	Network.cyclicFcfsInf(Matrix N, Matrix D, Matrix Z, Matrix S)	Creates a cyclic network with infinite server stations followed by FCFS queue stations with specified server counts.
static Network	Network.cyclicPs(Matrix N, Matrix D)	Creates a cyclic queueing network with Processor Sharing (PS) scheduling at all stations.
static Network	Network.cyclicPs(Matrix N, Matrix D, Matrix S)	Creates a cyclic queueing network with PS scheduling and specified server counts.
static Network	Network.cyclicPsInf(Matrix N, Matrix D, Matrix Z)	Creates a cyclic network with infinite server (delay) stations followed by PS queue stations.
static Network	Network.cyclicPsInf(Matrix N, Matrix D, Matrix Z, Matrix S)	Creates a cyclic network with infinite server stations followed by PS queue stations with specified server counts.
static Matrix	ModelAdapter.findPaths(NetworkStruct sn, Matrix P, int startNode, int endNode, int r, ArrayList<Integer> toMerge, Matrix QN, Matrix TN, double currentTime, Matrix fjclassmap, Matrix fjforkmap, Network nonfjmodel)	Finds the response times along each path leading out of startNode up to (and not including) endNode
static Matrix	ModelAdapter.findPathsCS(NetworkStruct sn, Matrix P, int curNode, int endNode, int curClass, ArrayList<Integer> toMerge, Matrix QN, Matrix TN, double currentTime, Matrix fjclassmap, Matrix fjforkmap, Network nonfjmodel)	Finds the response times along each path leading out of curNode up to (and not including) endNode Variant for models with class switching
Network.routingMatrixReturn	Network.getRoutingMatrix(Matrix arvRates, int returnVal)
void	Network.initFromAvgQLen(Matrix AvgQLen)
void	Network.initFromMarginal(Matrix n)
void	Network.initFromMarginalAndRunning(Matrix n, Matrix s)
void	Network.initFromMarginalAndStarted(Matrix n, Matrix s)
static Ret.FJApprox	ModelAdapter.mmt(Network model, Matrix forkLambda)	Fork-Join Transform approach to evaluate queueing networks including fork-join systems.
void	Network.refreshRoutingMatrix(Matrix rates)
Markovian	Environment.ResetEnvRatesFunction.reset(Markovian originalDist, Matrix QExit, Matrix UExit, Matrix TExit)
Matrix	Environment.ResetQueueLengthsFunction.reset(Matrix input)
void	RoutingMatrix.set(int classIndex1, int classIndex2, Matrix rt)
void	RoutingMatrix.set(JobClass jobclass1, JobClass jobclass2, Matrix rt)
void	RoutingMatrix.set(JobClass jobclass, Matrix rt)
void	Network.setConnectionMatrix(Matrix connection)
void	Network.setCsMatrix(Matrix csMatrix)
void	Region.setLinearConstraints(Matrix A, Matrix b)	Sets general linear admission constraints An <= b.
void	Event.setState(Matrix state)	Sets the system state matrix for this event.
void	ModeEvent.setState(Matrix state)
void	ClassSwitchMatrix.setTo(Matrix m1)
static Ret.FJsortForks	ModelAdapter.sort_forks(NetworkStruct sn, NetworkStruct nonfjstruct, Matrix fjforkmap, Matrix fjclassmap, Network nonfjmodel)	Determines a directed acyclic graph of relationships among fork nodes.
double	Network.sub_jsq(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)
double	Network.sub_kchoices(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)	Power-of-K choices marginal routing probability.
double	Network.sub_rl(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)	Reinforcement-learning routing marginal probability.
double	Network.sub_rr_wrr(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)
static Network	Network.tandem(Matrix lambda, Matrix D, SchedStrategy[] strategy, Matrix S)	Creates a tandem queueing network with specified arrival rates and service demands.
static Network	Network.tandemFcfs(Matrix lambda, Matrix D, Matrix S)
static Network	Network.tandemFcfsInf(Matrix lambda, Matrix D)	Creates a tandem network with FCFS infinite servers.
static Network	Network.tandemFcfsInf(Matrix lambda, Matrix D, Matrix Z)	Creates a tandem network with FCFS infinite servers and delay centers.
static Network	Network.tandemFcfsInf(Matrix lambda, Matrix D, Matrix Z, Matrix S)	Creates a tandem network with FCFS infinite servers, delays, and specified server counts.
static Network	Network.tandemPs(Matrix lambda, Matrix D, Matrix S)
static Network	Network.tandemPsInf(Matrix lambda, Matrix D)	Creates a tandem network with processor sharing infinite servers.
static Network	Network.tandemPsInf(Matrix lambda, Matrix D, Matrix Z)	Creates a tandem network with processor sharing infinite servers and delays.
static Network	Network.tandemPsInf(Matrix lambda, Matrix D, Matrix Z, Matrix S)

Method parameters in jline.lang with type arguments of type Matrix

Modifier and Type	Method	Description
double	Event.getProb(Pair<Map<Node,Matrix>,Map<Node,Matrix>> state)	Computes the probability of this event using the probability function and current system state.
double	Event.getProb(Pair<Map<Node,Matrix>,Map<Node,Matrix>> state)	Computes the probability of this event using the probability function and current system state.
void	Network.relinkFromRtorig(Map<JobClass,Map<JobClass,Matrix>> rtorig)	Relink the network from a modified rtorig map.
void	Event.setProbFun(SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double> probFun)	Sets the probability function to dynamically compute event probability based on system state.
void	Event.setProbFun(SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double> probFun)	Sets the probability function to dynamically compute event probability based on system state.
double	Network.sub_jsq(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)
double	Network.sub_kchoices(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)	Power-of-K choices marginal routing probability.
double	Network.sub_rl(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)	Reinforcement-learning routing marginal probability.
double	Network.sub_rr_wrr(int ind, int jnd, int r, int s, Matrix linksmat, Map<Node,Matrix> state_before, Map<Node,Matrix> state_after)
void	Network.updateRtorig(Map<JobClass,Map<JobClass,Matrix>> rtorig)	Updates sn.rtorig without replacing the entire NetworkStruct.

Constructors in jline.lang with parameters of type Matrix

Modifier	Constructor	Description
	AggregateChainResult(Network chainModel, Matrix alpha, ModelAdapter.DeaggInfo deaggInfo)
	ClassSwitchMatrix(Matrix matrix)
	Event(EventType event, int node, int jobclass, double prob, Matrix state, double t, double job)	Creates a new Event with all basic parameters specified.
	Event(EventType event, int node, int jobclass, SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double> probFun, Matrix state, double t, double job)	Creates a new Event where probability is determined by a function of system state.
	ModeEvent(EventType event, int node, int mode, double weight, double prob, Matrix state)
	ModeEvent(EventType event, int node, int mode, double weight, double prob, Matrix state, double t)
	ModeEvent(EventType event, int node, int mode, double weight, double prob, Matrix state, double t, double job)
	routingMatrixReturn(Matrix rt, Matrix rtnodes, Matrix linksmat, Matrix chains, Map<JobClass,Map<JobClass,Matrix>> rtNodesByClass, Map<Node,Map<Node,Matrix>> rtNodesByStation)

Constructor parameters in jline.lang with type arguments of type Matrix

Modifier	Constructor	Description
	Event(EventType event, int node, int jobclass, SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double> probFun, Matrix state, double t, double job)	Creates a new Event where probability is determined by a function of system state.
	Event(EventType event, int node, int jobclass, SerializableFunction<Pair<Map<Node,Matrix>,Map<Node,Matrix>>,Double> probFun, Matrix state, double t, double job)	Creates a new Event where probability is determined by a function of system state.
	routingMatrixReturn(Matrix rt, Matrix rtnodes, Matrix linksmat, Matrix chains, Map<JobClass,Map<JobClass,Matrix>> rtNodesByClass, Map<Node,Map<Node,Matrix>> rtNodesByStation)

Uses of Matrix in jline.lang.layered

Fields in jline.lang.layered declared as Matrix

Modifier and Type	Field	Description
Matrix	LayeredNetworkStruct.actphase
Matrix	LayeredNetworkStruct.actposttype
Matrix	LayeredNetworkStruct.actpretype
protected Matrix	Activity.asyncCallMeans
Matrix	LayeredNetworkStruct.callpair
Matrix	LayeredNetworkStruct.conntasks
Matrix	LayeredNetworkStruct.dag
Matrix	LayeredNetworkStruct.fanout
protected Matrix	Entry.forwardingProbs
Matrix	LayeredNetworkStruct.graph
Matrix	LayeredNetworkStruct.isasynccaller
Matrix	LayeredNetworkStruct.iscache
Matrix	LayeredNetworkStruct.iscaller
Matrix	LayeredNetworkStruct.isfunction
Matrix	LayeredNetworkStruct.isref
Matrix	LayeredNetworkStruct.issynccaller
Matrix	LayeredNetworkStruct.maxmult
Matrix	LayeredNetworkStruct.mult
Matrix	LayeredNetworkStruct.nitems
Matrix	LayeredNetworkStruct.parent
protected Matrix	ActivityPrecedence.postParams
protected Matrix	ActivityPrecedence.preParams
Matrix	LayeredNetworkStruct.repl
Matrix	LayeredNetworkStruct.replacement
Matrix	LayeredNetworkStruct.replacestrat
Matrix	LayeredNetworkStruct.replygraph
Matrix	LayeredNetworkStruct.schedid
protected Matrix	Activity.scheduling
protected Matrix	Entry.scheduling
protected Matrix	Activity.syncCallMeans
Matrix	LayeredNetworkStruct.taskgraph
Matrix	LayeredNetworkStruct.type

Fields in jline.lang.layered with type parameters of type Matrix

Modifier and Type	Field	Description
Map<Integer,Matrix>	LayeredNetworkStruct.actthink_params
Map<Integer,Matrix>	LayeredNetworkStruct.arrival_params
Map<Integer,Matrix>	LayeredNetworkStruct.callproc_params
Map<Integer,Matrix>	LayeredNetworkStruct.delayofftime_params
Map<Integer,Matrix>	LayeredNetworkStruct.hostdem_params
Map<Integer,Matrix>	LayeredNetworkStruct.itemproc_params
Map<Integer,Matrix>	LayeredNetworkStruct.setuptime_params
Map<Integer,Matrix>	LayeredNetworkStruct.think_params

Methods in jline.lang.layered that return Matrix

Modifier and Type	Method	Description
Matrix	Activity.getAsyncCallMeans()
Matrix	Entry.getForwardingProbs()	Get the matrix of forwarding probabilities.
Matrix	ActivityPrecedence.getPostParams()	Returns the parameters for the following activities.
Matrix	ActivityPrecedence.getPreParams()	Returns the parameters for the preceding activities.
Matrix	Activity.getSyncCallMeans()

Methods in jline.lang.layered with parameters of type Matrix

Modifier and Type	Method	Description
static ActivityPrecedence	ActivityPrecedence.AndFork(String preAct, List<String> postActs, Matrix fanout)	Creates an ActivityPrecedence object representing an AND-fork relationship with a specified fanout matrix.
static ActivityPrecedence	ActivityPrecedence.AndFork(Activity preAct, List<Activity> postActs, Matrix fanout)	Creates an ActivityPrecedence object representing an AND-fork relationship with a specified fanout matrix.
static ActivityPrecedence	ActivityPrecedence.AndJoin(List<String> preActs, String postAct, Matrix quorum)	Creates an ActivityPrecedence object representing an AND-join relationship with a specified quorum matrix.
static ActivityPrecedence	ActivityPrecedence.AndJoin(List<Activity> preActs, Activity postAct, Matrix quorum)	Creates an ActivityPrecedence object representing an AND-join relationship with a specified quorum matrix.
static ActivityPrecedence	ActivityPrecedence.fromActivities(List<Activity> preActs, List<Activity> postActs, String preType, String postType, Matrix preParams)	Creates an ActivityPrecedence with Activity objects, without postParams.
static ActivityPrecedence	ActivityPrecedence.fromActivities(List<Activity> preActs, List<Activity> postActs, String preType, String postType, Matrix preParams, Matrix postParams)	Creates an ActivityPrecedence with Activity objects.
static ActivityPrecedence	ActivityPrecedence.Loop(String preAct, String loopAct, String endAct, Matrix nloops)	Creates an ActivityPrecedence object representing a loop relationship.
static ActivityPrecedence	ActivityPrecedence.Loop(String preAct, List<String> postActs, String endAct, Matrix nloops)
static ActivityPrecedence	ActivityPrecedence.Loop(String preAct, List<String> postActs, Matrix nloops)	Creates an ActivityPrecedence object representing a loop relationship.
static ActivityPrecedence	ActivityPrecedence.Loop(Activity preAct, List<Activity> postActs, Activity endAct, Matrix nloops)
static ActivityPrecedence	ActivityPrecedence.Loop(Activity preAct, List<Activity> postActs, Matrix nloops)	Creates an ActivityPrecedence object representing a loop relationship.
static ActivityPrecedence	ActivityPrecedence.Loop(Activity preAct, Activity loopAct, Activity endAct, Matrix nloops)	Creates an ActivityPrecedence object representing a loop relationship.
static ActivityPrecedence	ActivityPrecedence.OrFork(String preAct, List<String> postActs, Matrix probs)	Creates an ActivityPrecedence object representing an OR-fork relationship with a specified probability matrix.
static ActivityPrecedence	ActivityPrecedence.OrFork(Activity preAct, List<Activity> postActs, Matrix probs)	Creates an ActivityPrecedence object representing an OR-fork relationship with a specified probability matrix.
static DiscreteDistribution	LayeredNetwork.reconstructDiscreteDistribution(ProcessType type, Matrix params, Double mean)	Reconstruct a DiscreteDistribution object from primitive parameters.
static Distribution	LayeredNetwork.reconstructDistribution(ProcessType type, Matrix params, Double mean, Double scv, MatrixCell proc)	Reconstruct a Distribution object from primitive parameters.
Activity	Activity.setAsyncCallMeans(Matrix asyncCallMeans)
Activity	Activity.setSyncCallMeans(Matrix syncCallMeans)
static ActivityPrecedence	ActivityPrecedence.Xor(String preAct, List<String> postActs, Matrix probs)	Creates an ActivityPrecedence object representing an XOR relationship.
static ActivityPrecedence	ActivityPrecedence.Xor(Activity preAct, List<Activity> postActs, Matrix probs)	Creates an ActivityPrecedence object representing an XOR relationship.

Constructors in jline.lang.layered with parameters of type Matrix

Modifier	Constructor	Description
	ActivityPrecedence(List<String> preActs, List<String> postActs, String preType, String postType, Matrix preParams)	Constructs an ActivityPrecedence with the specified parameters, without postParams.
	ActivityPrecedence(List<String> preActs, List<String> postActs, String preType, String postType, Matrix preParams, Matrix postParams)	Constructs an ActivityPrecedence with the specified parameters.

Uses of Matrix in jline.lang.nodeparam

Fields in jline.lang.nodeparam declared as Matrix

Modifier and Type	Field	Description
Matrix[][]	CacheNodeParam.accost	Access cost matrix for cache items by class [items x classes x servers]
Matrix	CacheNodeParam.actualhitprob	Actual hit probabilities computed during analysis [items x classes]
Matrix	CacheNodeParam.actualmissprob	Actual miss probabilities computed during analysis [items x classes]
Matrix	TransitionNodeParam.fireweight
Matrix	TransitionNodeParam.firingphases
Matrix	TransitionNodeParam.firingprio
Matrix	CacheNodeParam.hitclass	Job class routing matrix for cache hits [items x classes]
Matrix	CacheNodeParam.itemcap	Capacity matrix specifying maximum number of each item type [items x 1]
Matrix	CacheNodeParam.missclass	Job class routing matrix for cache misses [items x classes]
Matrix	TransitionNodeParam.nmodeservers

Fields in jline.lang.nodeparam with type parameters of type Matrix

Modifier and Type	Field	Description
List<Matrix>	TransitionNodeParam.enabling
List<Matrix>	TransitionNodeParam.firing
Map<Mode,Matrix>	TransitionNodeParam.firingpie
List<Matrix>	TransitionNodeParam.inhibiting

Uses of Matrix in jline.lang.nodes

Fields in jline.lang.nodes declared as Matrix

Modifier and Type	Field	Description
Matrix[][]	Cache.accessProb
Matrix	Transition.firingPriorities
Matrix	Transition.firingWeights
protected Matrix	Station.ljcdCutoffs
protected Matrix	Station.ljdCutoffs
protected Matrix	Station.ljdScaling
protected Matrix	Station.lldScaling
protected Matrix	Node.state

Fields in jline.lang.nodes with type parameters of type Matrix

Modifier and Type	Field	Description
Map<Mode,Matrix>	Transition.enablingConditions
Map<Mode,Matrix>	Transition.firingOutcomes
Map<Mode,Matrix>	Transition.inhibitingConditions
protected SerializableFunction<Matrix,Double>	Station.lcdScaling
protected Map<JobClass,Matrix>	Station.ljcdScaling

Methods in jline.lang.nodes that return Matrix

Modifier and Type	Method	Description
Matrix	Cache.getAccessProb(int i, int j)	Gets the access probability matrix for a specific cache level and job class.
Matrix[]	Cache.getGraph()	Gets the graph structure defining the cache organization.
Matrix	Cache.getHitClass()	For an incoming job of class r, HITCLASS[r] is the new class of that job after a hit
Matrix	Cache.getHitRatio()	Gets the actual hit probability/ratio for each job class.
Matrix	Cache.getItemLevelCap()	Gets the capacity configuration for each cache level.
Matrix	Station.getLimitedJointClassDependenceCutoffs()	Gets the per-class cutoffs for joint class dependence.
Matrix	Station.getLimitedJointDependence()	Gets the limited joint-dependent scaling matrix for this station.
Matrix	Station.getLimitedJointDependenceCutoffs()	Gets the per-class cutoffs for joint dependence.
Matrix	Station.getLimitedLoadDependence()	Gets the limited load-dependent scaling matrix for this station.
Matrix	Cache.getMissClass()	For an incoming job of class r, MISSCLASS[r] is the new class of that job after a miss
Matrix	Cache.getMissRatio()	Gets the actual miss probability/ratio for each job class.
Matrix	Transition.getNumberOfModeServers()
Matrix	Node.getState()	Gets the current state of this node.
Matrix	StatefulNode.getState()
Matrix	StatefulNode.getStatePrior()
Matrix	StatefulNode.getStateSpace()

Methods in jline.lang.nodes that return types with arguments of type Matrix

Modifier and Type	Method	Description
SerializableFunction<Matrix,Double>	Station.getLimitedClassDependence()	Gets the limited class-dependent scaling function for this station.
Map<JobClass,Matrix>	Station.getLimitedJointClassDependence()	Gets the limited joint-class-dependent scaling tables for this station.

Methods in jline.lang.nodes with parameters of type Matrix

Modifier and Type	Method	Description
void	Cache.setAccessProb(Matrix[][] R)	Sets the access probability matrices for all cache levels and job classes.
void	Queue.setJointClassDependence(Map<JobClass,Matrix> scalingTables, Matrix cutoffs)	Sets per-class joint class-dependent scaling for service rates.
void	Queue.setJointDependence(Matrix scalingTable)	Sets joint class-dependent scaling with auto-computed cutoffs.
void	Queue.setJointDependence(Matrix scalingTable, Matrix cutoffs)	Sets joint class-dependent scaling for service rates using a lookup table.
void	Station.setLimitedJointClassDependence(Map<JobClass,Matrix> scalingTables, Matrix cutoffs)	Sets the limited joint-class-dependent scaling for this station.
void	Station.setLimitedJointDependence(Matrix scalingTable, Matrix cutoffs)	Sets the limited joint-dependent scaling for this station.
void	Station.setLimitedLoadDependence(Matrix alpha)	Sets the limited load-dependent scaling matrix for this station.
void	Queue.setLoadDependence(Matrix alpha)	Sets load-dependent service rate scaling factors.
void	Cache.setResultHitProb(Matrix actualHitProb)	Sets the actual hit probabilities from simulation or analysis results.
void	Cache.setResultMissProb(Matrix actualMissProb)	Sets the actual miss probabilities from simulation or analysis results.
void	Node.setRLRouting(JobClass jobClass, Matrix valueFunction, int[] vfShape, int[] nodesNeedAction, int stateSize)	Configures reinforcement-learning routing for a job class.
void	Node.setState(Matrix state)	Sets the state of this node.
void	StatefulNode.setState(Matrix state)
void	StatefulNode.setStatePrior(Matrix prior)
void	StatefulNode.setStateSpace(Matrix space)

Method parameters in jline.lang.nodes with type arguments of type Matrix

Modifier and Type	Method	Description
void	Queue.setClassDependence(SerializableFunction<Matrix,Double> beta)	Sets a class-dependent scaling function for service rates.
void	Queue.setJointClassDependence(Map<JobClass,Matrix> scalingTables, Matrix cutoffs)	Sets per-class joint class-dependent scaling for service rates.
void	Station.setLimitedClassDependence(SerializableFunction<Matrix,Double> gamma)	Sets the limited class-dependent scaling function for this station.
void	Station.setLimitedJointClassDependence(Map<JobClass,Matrix> scalingTables, Matrix cutoffs)	Sets the limited joint-class-dependent scaling for this station.

Constructors in jline.lang.nodes with parameters of type Matrix

Modifier	Constructor	Description
	Cache(Network model, String name, int nitems, int itemLevelCap, ReplacementStrategy replPolicy, Matrix[] graph)	Creates a single-level cache with the specified item capacity, replacement policy, and graph structure.
	Cache(Network model, String name, int nitems, Matrix itemLevelCap, ReplacementStrategy replPolicy)	Creates a multi-level cache with different capacities per level and a replacement policy.
	Cache(Network model, String name, int nitems, Matrix itemLevelCap, ReplacementStrategy replPolicy, Matrix[] graph)	Creates a multi-level cache with different capacities per level, replacement policy, and graph structure.
	ClassSwitch(Network model, String name, Matrix csFun)

Uses of Matrix in jline.lang.processes

Fields in jline.lang.processes declared as Matrix

Modifier and Type	Field	Description
protected Matrix	EmpiricalCDF.data
protected Matrix	MarkovProcess.infGen
protected Matrix	MarkovChain.stateSpace
protected Matrix	MarkovProcess.stateSpace
protected Matrix	MarkovChain.transMat

Fields in jline.lang.processes with type parameters of type Matrix

Modifier and Type	Field	Description
protected Map<Integer,Matrix>	Det.process

Methods in jline.lang.processes that return Matrix

Modifier and Type	Method	Description
Matrix	Markovian.acf(int maxLag)	Kotlin-style property alias for getACF()
Matrix	DMAP.D(int i)
Matrix	MAP.D(int i)
Matrix	Marked.D(int i)
Matrix	Marked.D(int i, int k)
Matrix	Markovian.D(int i)	Gets the i-th matrix of the Markovian arrival process representation.
Matrix	MMPP2.D(int i)
Matrix	Markovian.embedded()	Kotlin-style property alias for getEmbedded()
Matrix	Markovian.embeddedProb()	Kotlin-style property alias for getEmbeddedProb()
Matrix	MAP.evalACFT(int[] lags, double timescale)	Evaluates the autocorrelation function at given lags and timescale.
Matrix	MarkovModulated.evalACFT(int[] lags, double timescale)
Matrix	MMPP2.evalACFT(int[] lags, double timescale)
Matrix	APH.evalCDFMatrix()	Evaluates the CDF at default time points and returns as a Matrix.
Matrix	APH.evalCDFMatrix(double[] timePoints)	Evaluates the CDF at specified time points and returns as a Matrix.
Matrix	DiscreteDistribution.evalPMF(List<Double> t)
Matrix	DiscreteSampler.evalPMF(List<Double> t)
Matrix	Zipf.evalPMF()
Matrix	Zipf.evalPMF(List<Double> t)	Evaluates the probability mass function at t
Matrix	ME.getA()	Gets the matrix parameter A.
Matrix	Markovian.getACF(Matrix lags)	Gets the autocorrelation function at the specified lags.
Matrix	ME.getAlpha()	Gets the initial vector alpha.
Matrix	BMAP.getBatchMatrix(int batchSize)	Get the D_k matrix for batch size k
Matrix	MultivariateNormal.getCorrelation()	Gets the correlation matrix from the covariance matrix.
Matrix	MultivariateNormal.getCovariance()	Gets the covariance matrix.
Matrix	Marked.getD1k(int k)
Matrix	EmpiricalCDF.getData()	Get the empirical data
Matrix	Markovian.getEmbedded()	Gets the embedded Markov chain transition matrix.
Matrix	MMPP2.getEmbedded()
Matrix	Markovian.getEmbeddedProb()	Gets the stationary probability vector of the embedded Markov chain.
Matrix	MMPP2.getEmbeddedProb()
Matrix	MarkovProcess.getGenerator()	Get the infinitesimal generator matrix
Matrix	RAP.getH0()	Gets the H0 matrix (hidden transition rates).
Matrix	RAP.getH1()	Gets the H1 matrix (visible transition rates).
Matrix	APH.getInitProb()
Matrix	Markovian.getInitProb()	Gets the initial probability vector.
Matrix	PH.getInitProb()
Matrix	MultivariateNormal.getMeanVector()	Gets the mean vector.
Matrix	Coxian.getMu()
Matrix	DMAP.getMu()	Row sums of (I - D0).
Matrix	Markovian.getMu()	Gets the diagonal rate matrix containing the negative diagonal elements of D0.
Matrix	Coxian.getPhi()
Matrix	Markovian.getPhi()	Gets the exit probability vector (phi).
Matrix	MarkovProcess.getProbState(Matrix state)	Get probability of a specific state using Cramer's rule
Matrix	MarkovChain.getStateSpace()	Get the state space
Matrix	MarkovProcess.getStateSpace()	Get the state space
Matrix	APH.getSubgenerator()
Matrix	Markovian.getSubgenerator()
Matrix	PH.getSubgenerator()
Matrix	DMAP.getTransitionMatrix()	Embedded chain P = (I - D0)^{-1} * D1.
Matrix	MarkovChain.getTransMat()	Get the transition matrix
Matrix	MMAP.getTypeMatrix(int type)	Get the D_k matrix for arrival type k
Matrix	APH.initProb()	Kotlin-style property alias for getInitProb()
Matrix	Markovian.initProb()	Kotlin-style property alias for getInitProb()
Matrix	PH.initProb()	Kotlin-style property alias for getInitProb()
Matrix	Coxian.mu()	Kotlin-style property alias for getMu()
Matrix	Markovian.mu()	Kotlin-style property alias for getMu()
Matrix	Coxian.phi()	Kotlin-style property alias for getPhi()
Matrix	Markovian.phi()	Kotlin-style property alias for getPhi()
Matrix	MMDP.Q()	Returns the generator matrix Q.
Matrix	MMDP2.Q()	Returns the generator matrix Q (closed-form for 2 states).
Matrix	MMDP.r()	Returns the rate vector (diagonal of R).
Matrix	MMDP2.r()	Returns the rate vector (diagonal of R).
Matrix	MMDP.R()	Returns the rate matrix R (diagonal).
Matrix	MMDP2.R()	Returns the rate matrix R (diagonal, closed-form for 2 states).
Matrix	MarkovChain.sample()	Sample from the DTMC
Matrix	MarkovChain.sample(int n)	Sample n steps from the DTMC starting from initial distribution
Matrix	MarkovChain.sample(int n, Matrix pi0, Random random)	Sample n steps from the DTMC
Matrix	MarkovProcess.sample()	Sample from the CTMC
Matrix	MarkovProcess.sample(int n)	Sample n state transitions from the CTMC starting from steady-state
Matrix	MarkovProcess.sample(int n, Matrix pi0, Random random)	Sample n state transitions from the CTMC
Matrix	MultivariateNormal.sampleMatrix(int n, Random random)	Generates random samples from the distribution.
Matrix	MarkovProcess.solve()	Solve the CTMC for steady-state probabilities
Matrix	Markovian.subgenerator()	Kotlin-style property alias for getSubgenerator()
Matrix	PH.subgenerator()	Kotlin-style property alias for getSubgenerator()
Matrix	GMM.toMatrix()	Converts this GMM to a simplified matrix representation.

Methods in jline.lang.processes that return types with arguments of type Matrix

Modifier and Type	Method	Description
Map<Integer,Matrix>	Immediate.getPH()
Map<Integer,Matrix>	Det.getProcess()	Gets the matrix representation of this deterministic process (for PH compatibility).
Map<Integer,Matrix>	Det.process()	Kotlin-style property alias for getProcess()

Methods in jline.lang.processes with parameters of type Matrix

Modifier and Type	Method	Description
double	MultivariateNormal.evalPDF(Matrix x)	Evaluates the probability density function.
static MMAP	MMAP.fromMAPs(Matrix D0, Matrix D1, Matrix D2)	Factory method to create a simple 2-type MMAP from two MAPs
static BMAP	BMAP.fromMAPWithBatchPMF(Matrix D0, Matrix D1, int[] batchSizes, double[] pmf)	Factory method to create BMAP from a base MAP and batch size distribution Given a base MAP (D0_base, D1_base) for inter-batch arrivals and a batch size distribution, constructs the BMAP by scaling: Dk = D1_base * pmf[k-1]
static GMM	GMM.fromMatrix(Matrix sgmm)	Creates a GMM from a simplified matrix representation.
static MarkovChain	MarkovChain.fromSampleSysAggr(Matrix samples)	Create DTMC from sample system aggregation
static MarkovChain	MarkovChain.fromSampleSysAggr(Matrix samples, int numStates)	Create DTMC from sample system aggregation
static MarkovProcess	MarkovProcess.fromSampleSysAggr(Matrix samples)	Create CTMC from sample system aggregation (assuming unit sojourn times)
static MarkovProcess	MarkovProcess.fromSampleSysAggr(Matrix samples, Matrix sojournTimes)	Create CTMC from sample system aggregation
static MarkovProcess	MarkovProcess.fromSampleSysAggr(Matrix samples, Matrix sojournTimes, int numStates)	Create CTMC from sample system aggregation
Matrix	Markovian.getACF(Matrix lags)	Gets the autocorrelation function at the specified lags.
double	MMPP2.getACFDecay(Matrix lags)
Matrix	MarkovProcess.getProbState(Matrix state)	Get probability of a specific state using Cramer's rule
static boolean	MMDP.isFeasible(Matrix Q, Matrix R)	Checks if the given (Q, R) matrices define a valid MMDP.
Matrix	MarkovChain.sample(int n, Matrix pi0, Random random)	Sample n steps from the DTMC
Matrix	MarkovProcess.sample(int n, Matrix pi0, Random random)	Sample n state transitions from the CTMC
void	MarkovChain.setStateSpace(Matrix stateSpace)	Set the state space
void	MarkovProcess.setStateSpace(Matrix stateSpace)	Set the state space

Method parameters in jline.lang.processes with type arguments of type Matrix

Modifier and Type	Method	Description
void	Det.setProcess(Map<Integer,Matrix> proc)	Sets the matrix representation of this deterministic process.

Constructors in jline.lang.processes with parameters of type Matrix

Modifier	Constructor	Description
	APH(List<Double> alpha, Matrix T)
	APH(Matrix alpha, Matrix T)
	BMAP(Matrix D0, Matrix... Dk)	Construct a BMAP from D0 and variable number of Dk matrices
	Coxian(Matrix mu0, Matrix phi0)
	DiscreteSampler(Matrix p)
	DiscreteSampler(Matrix p, Matrix x)	Constructs a discrete distribution from a finite probability vector p at the points specified in vector x
	DMAP(Matrix D0, Matrix D1)
	EmpiricalCDF(Matrix xdata)	Creates an EmpiricalCDF with the given data
	EmpiricalCDF(Matrix cdfdata, Matrix xdata)	Creates an EmpiricalCDF with separate CDF and value data
	MAP(Matrix D0, Matrix D1)
	MarkedMarkovProcess(Matrix infGen, MatrixCell eventFilt, List<Map<String,Object>> evs)	Creates a MarkedCTMC with the specified generator, event filters, and events
	MarkedMarkovProcess(Matrix infGen, MatrixCell eventFilt, List<Map<String,Object>> evs, boolean isFinite)	Creates a MarkedCTMC with the specified generator, event filters, events, and finite flag
	MarkedMarkovProcess(Matrix infGen, MatrixCell eventFilt, List<Map<String,Object>> evs, boolean isFinite, Matrix stateSpace)	Creates a MarkedCTMC with the specified generator, event filters, events, finite flag, and state space
	MarkovChain(Matrix transMat)	Creates a DTMC with the specified transition matrix
	MarkovChain(Matrix transMat, boolean isFinite)	Creates a DTMC with the specified transition matrix and finite flag
	MarkovProcess(Matrix infGen)	Creates a CTMC with the specified infinitesimal generator
	MarkovProcess(Matrix infGen, boolean isFinite)	Creates a CTMC with the specified infinitesimal generator and finite flag
	MarkovProcess(Matrix infGen, boolean isFinite, Matrix stateSpace)	Creates a CTMC with the specified infinitesimal generator, finite flag, and state space
	ME(Matrix alpha, Matrix A)	Creates a Matrix Exponential distribution with specified initial vector and matrix parameter.
	MMAP(Matrix D0, Matrix... Dk)	Construct an MMAP from D0 and variable number of Dk matrices
	MMDP(Matrix Q, Matrix R)	Creates an MMDP with specified generator Q and rate matrix R.
	MultivariateNormal(double[] mu, Matrix Sigma)	Creates a multivariate normal distribution.
	MultivariateNormal(Matrix mu, Matrix Sigma)	Creates a multivariate normal distribution.
	PH(Matrix alpha, Matrix T)
	RAP(Matrix H0, Matrix H1)	Creates a Rational Arrival Process with specified H0 and H1 matrices.

Uses of Matrix in jline.lang.reward

Methods in jline.lang.reward with parameters of type Matrix

Modifier and Type	Method	Description
double	RewardFunction.compute(Matrix state, NetworkStruct sn)	Compute the reward value for a given state.

Uses of Matrix in jline.lang.sections

Fields in jline.lang.sections declared as Matrix

Modifier and Type	Field	Description
Matrix	CacheClassSwitcher.actualHitProb
Matrix	CacheClassSwitcher.actualMissProb
Matrix	CacheClassSwitcher.hitClass
Matrix	CacheClassSwitcher.missClass
Matrix	CSFunInput.state	Optional state matrix
Matrix	CSFunInput.statedep	Optional state-dependent matrix

Methods in jline.lang.sections with parameters of type Matrix

Modifier and Type	Method	Description
double	CacheClassSwitcher.simpleHitMiss(int r, int s, Matrix state)
double	CacheClassSwitcher.simpleHitMiss(int r, int s, Matrix state, Matrix statep)
void	StatelessClassSwitcher.updateClassSwitch(Matrix csMatrix)

Constructors in jline.lang.sections with parameters of type Matrix

Modifier	Constructor	Description
	CacheClassSwitcher(List<JobClass> jobClasses, int items, Matrix capacity)
	CacheClassSwitcher(List<JobClass> jobClasses, int items, Matrix capacity, int levels)
	CSFunInput(int r, int s, Matrix state, Matrix statedep)	Creates a new CSFunInput.
	StatelessClassSwitcher(List<JobClass> jobClasses, Matrix csMatrix)

Uses of Matrix in jline.lang.state

Fields in jline.lang.state declared as Matrix

Modifier and Type	Field	Description
Matrix	State.StateSpaceGeneratorResult.Adj
final Matrix	State.spaceGeneratorNodesResult.capacityc
final Matrix	EventCacheKey.inspace
Matrix	State.StateMarginalStatistics.ni
Matrix	State.StateMarginalStatistics.nir
final Matrix	AfterGlobalEvent.AfterGlobalEventResult.outprob	Probability matrix for each resulting state transition.
final Matrix	State.EventHandleResult.outprob
final Matrix	AfterGlobalEvent.AfterGlobalEventResult.outrate	Transition rates matrix for each resulting state.
final Matrix	State.EventHandleResult.outrate
final Matrix	State.EventHandleResult.outspace
Matrix	State.StateMarginalStatistics.sir
Matrix	State.StateSpaceGeneratorResult.SS
Matrix	State.StateSpaceGeneratorResult.SSh

Fields in jline.lang.state with type parameters of type Matrix

Modifier and Type	Field	Description
final Map<StatefulNode,Matrix>	State.initialState
final Map<StatefulNode,Matrix>	State.initialStateSpace
List<Matrix>	State.StateMarginalStatistics.kir
final Map<StatefulNode,Matrix>	State.spaceGeneratorNodesResult.nodeStateSpace
final List<Matrix>	AfterGlobalEvent.AfterGlobalEventResult.outglspace	Updated global state space after event processing.
final Map<StatefulNode,Matrix>	State.priorInitialState
Map<StatefulNode,Matrix>	State.StateSpaceGeneratorResult.QNC.space

Methods in jline.lang.state that return Matrix

Modifier and Type	Method	Description
static Matrix	FromMarginal.fromMarginal(NetworkStruct sn, int ind, Matrix n)
static Matrix	FromMarginal.fromMarginalAndRunning(Network sn, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndRunning(NetworkStruct sn, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndRunning(NetworkStruct sn, int ind, Matrix n, Matrix s, boolean optionsForce)
static Matrix	FromMarginal.fromMarginalAndStarted(Network network, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndStarted(NetworkStruct sn, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndStarted(NetworkStruct sn, int ind, Matrix n, Matrix s, Boolean optionsForce)
static Matrix	FromMarginal.fromMarginalBounds(NetworkStruct sn, int ind, Matrix ub, double cap, SolverOptions options)
static Matrix	State.spaceCachePublic(int n, Matrix m)	Make spaceCache method public Generates cache state space
static Matrix	State.spaceClosedMulti(int M, Matrix N)
static Matrix	State.spaceClosedMultiCS(int M, Matrix N, Matrix chains)
static Matrix	State.spaceClosedSinglePublic(int M, int N)	Make spaceClosedSingle method public Generates state space for single-class closed networks
static Matrix	State.spaceLocalVarsPublic(NetworkStruct sn, int ind)	Make spaceLocalVars method public Generates local variable state spaces

Methods in jline.lang.state with parameters of type Matrix

Modifier and Type	Method	Description
static Ret.EventResult	State.afterEvent(NetworkStruct sn, int ind, Matrix inspace, EventType event, int jobClass, boolean isSimulation)
static Ret.EventResult	State.afterEvent(NetworkStruct sn, int ind, Matrix inspace, EventType event, int jobClass, boolean isSimulation, EventCache eventCache)
static int	AfterEventCache.cpos(Matrix matrix, int i, int j)
static Matrix	FromMarginal.fromMarginal(NetworkStruct sn, int ind, Matrix n)
static Matrix	FromMarginal.fromMarginalAndRunning(Network sn, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndRunning(NetworkStruct sn, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndRunning(NetworkStruct sn, int ind, Matrix n, Matrix s, boolean optionsForce)
static Matrix	FromMarginal.fromMarginalAndStarted(Network network, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndStarted(NetworkStruct sn, int ind, Matrix n, Matrix s)
static Matrix	FromMarginal.fromMarginalAndStarted(NetworkStruct sn, int ind, Matrix n, Matrix s, Boolean optionsForce)
static Matrix	FromMarginal.fromMarginalBounds(NetworkStruct sn, int ind, Matrix ub, double cap, SolverOptions options)
static Ret.getHashOrAddResult	State.getHashOrAdd(NetworkStruct sn, int ind, Matrix inspace)	Get hash ID for a state space, or add the state to the space if not found Migrated from MATLAB getHashOrAdd.m
protected static State.EventHandleResult	State.handleEnableEvent(NetworkStruct sn, int ind, GlobalSync glevent, List<Matrix> glspace, List<Matrix> outglspace, Matrix inspace, Matrix spaceBuf, Matrix spaceSrv, Matrix spaceVar, Matrix fK, Matrix fKs, int mode, TransitionNodeParam transParam, int R)	Handles ENABLE events for transitions in Stochastic Petri Net (SPN) event processing.
protected static State.EventHandleResult	State.handleFireEvent(NetworkStruct sn, int ind, GlobalSync glevent, List<Matrix> glspace, List<Matrix> outglspace, Matrix inspace, Matrix spaceBuf, Matrix spaceSrv, Matrix spaceVar, Matrix fK, Matrix fKs, int mode, TransitionNodeParam transParam, int R)	Handles FIRE events for transitions in Stochastic Petri Net (SPN) event processing.
static boolean	State.isValid(Network sn, Matrix n, Matrix s)
static boolean	State.isValid(NetworkStruct sn, Matrix n, Matrix s)
static Matrix	State.spaceCachePublic(int n, Matrix m)	Make spaceCache method public Generates cache state space
static Matrix	State.spaceClosedMulti(int M, Matrix N)
static Matrix	State.spaceClosedMultiCS(int M, Matrix N, Matrix chains)
static State.StateSpaceGeneratorResult	State.spaceGenerator(NetworkStruct sn, Matrix cutoff, SolverOptions options)	Generates the state space for a queueing network using a matrix cutoff.
static State.spaceGeneratorNodesResult	State.spaceGeneratorNodes(NetworkStruct sn, Matrix cutoff, SolverOptions options)
static State.StateMarginalStatistics	ToMarginal.toMarginal(NetworkStruct sn, int ind, Matrix state_i, Matrix phasesz, Matrix phaseshift, Matrix space_buf, Matrix space_srv, Matrix space_var)	Computes marginal statistics for a stateful node in a Stochastic Petri Net.
static State.StateMarginalStatistics	ToMarginal.toMarginalAggr(NetworkStruct sn, int ind, Matrix state_i, Matrix K, Matrix Ks, Matrix space_buf, Matrix space_srv, Matrix space_var)	Computes aggregated marginal statistics for a stateful node using specified aggregation weights.

Method parameters in jline.lang.state with type arguments of type Matrix

Modifier and Type	Method	Description
static AfterGlobalEvent.AfterGlobalEventResult	AfterGlobalEvent.afterGlobalEvent(NetworkStruct sn, int ind, List<Matrix> glspace, GlobalSync glevent, boolean isSimulation)	Processes a global event in a Stochastic Petri Net (SPN) and computes the resulting state space.
static Map<StatefulNode,Map<String,Integer>>	State.buildSpaceHashMap(Map<StatefulNode,Matrix> space)
protected static State.EventHandleResult	State.handleEnableEvent(NetworkStruct sn, int ind, GlobalSync glevent, List<Matrix> glspace, List<Matrix> outglspace, Matrix inspace, Matrix spaceBuf, Matrix spaceSrv, Matrix spaceVar, Matrix fK, Matrix fKs, int mode, TransitionNodeParam transParam, int R)	Handles ENABLE events for transitions in Stochastic Petri Net (SPN) event processing.
protected static State.EventHandleResult	State.handleFireEvent(NetworkStruct sn, int ind, GlobalSync glevent, List<Matrix> glspace, List<Matrix> outglspace, Matrix inspace, Matrix spaceBuf, Matrix spaceSrv, Matrix spaceVar, Matrix fK, Matrix fKs, int mode, TransitionNodeParam transParam, int R)	Handles FIRE events for transitions in Stochastic Petri Net (SPN) event processing.

Constructors in jline.lang.state with parameters of type Matrix

Modifier	Constructor	Description
	AfterGlobalEventResult(List<Matrix> outglspace, Matrix outrate, Matrix outprob)	Constructs a new result container for global event processing.
	EventCacheKey(int ind, Matrix inspace, EventType event, int jobClass, boolean isSimulation)
	EventHandleResult(Matrix outspace, Matrix outrate, Matrix outprob)
	spaceGeneratorNodesResult(Map<StatefulNode,Matrix> nodeStateSpace, NetworkStruct sn, Matrix capacityc)
	StateMarginalStatistics(Matrix ni, Matrix nir, Matrix sir, List<Matrix> kir)
	StateSpaceGeneratorResult(Matrix ss, Matrix sSh, NetworkStruct sn)

Constructor parameters in jline.lang.state with type arguments of type Matrix

Modifier	Constructor	Description
	AfterGlobalEventResult(List<Matrix> outglspace, Matrix outrate, Matrix outprob)	Constructs a new result container for global event processing.
	spaceGeneratorNodesResult(Map<StatefulNode,Matrix> nodeStateSpace, NetworkStruct sn, Matrix capacityc)
	State(Map<StatefulNode,Matrix> initialState, Map<StatefulNode,Matrix> priorInitialState, Map<StatefulNode,Matrix> initialStateSpace)
	StateMarginalStatistics(Matrix ni, Matrix nir, Matrix sir, List<Matrix> kir)

Uses of Matrix in jline.lang.workflow

Methods in jline.lang.workflow that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Workflow.composeParallel(Matrix alpha1, Matrix T1, Matrix alpha2, Matrix T2)
static Pair<Matrix,Matrix>	Workflow.composeParallel(Matrix alpha1, Matrix T1, Matrix alpha2, Matrix T2)
static Pair<Matrix,Matrix>	Workflow.composeRepeat(Matrix alpha, Matrix T, int count)
static Pair<Matrix,Matrix>	Workflow.composeRepeat(Matrix alpha, Matrix T, int count)
static Pair<Matrix,Matrix>	Workflow.composeSerial(Matrix alpha1, Matrix T1, Matrix alpha2, Matrix T2)
static Pair<Matrix,Matrix>	Workflow.composeSerial(Matrix alpha1, Matrix T1, Matrix alpha2, Matrix T2)
Pair<Matrix,Matrix>	WorkflowActivity.getPHRepresentation()
Pair<Matrix,Matrix>	WorkflowActivity.getPHRepresentation()

Methods in jline.lang.workflow with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Workflow.composeParallel(Matrix alpha1, Matrix T1, Matrix alpha2, Matrix T2)
static Pair<Matrix,Matrix>	Workflow.composeRepeat(Matrix alpha, Matrix T, int count)
static Pair<Matrix,Matrix>	Workflow.composeSerial(Matrix alpha1, Matrix T1, Matrix alpha2, Matrix T2)

Uses of Matrix in jline.lib.butools

Methods in jline.lib.butools that return Matrix

Modifier and Type	Method	Description
static Matrix	FactorialMomsFromMoms.factorialMomsFromMoms(Matrix m)	Returns the factorial moments given the raw moments.
static Matrix	HankelMomsFromMoms.hankelMomsFromMoms(Matrix m)	Returns the Hankel moments given the raw moments.
static Matrix	JFactorialMomsFromJMoms.jFactorialMomsFromJMoms(Matrix jm)	Returns the lag-1 joint factorial moments given the lag-1 joint raw moments.
static Matrix	JMomsFromJFactorialMoms.jMomsFromJFactorialMoms(Matrix jfm)	Returns the lag-1 joint raw moments given the lag-1 joint factorial moments.
static Matrix	MomsFromFactorialMoms.MomsFromFactorialMoms(Matrix fm)	Returns the raw moments given the factorial moments.
static Matrix	MomsFromHankelMoms.momsFromHankelMoms(Matrix hm)	Returns the raw moments given the Hankel moments.
static Matrix	MomsFromNormMoms.momsFromNormMoms(Matrix nm)	Returns the raw moments given the normalized moments.
static Matrix	MomsFromReducedMoms.momsFromReducedMoms(Matrix rm)	Returns the raw moments given the reduced moments.
static Matrix	Poly.poly(Matrix x)
static Matrix	ReducedMomsFromMoms.reducedMomsFromMoms(Matrix m)	Returns the reduced moments given the raw moments.
static Matrix	SimilarityMatrixForVectors.SimilarityMatrixForVectors(Matrix vecA, Matrix vecB)

Methods in jline.lib.butools that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Map<String,Matrix>	FluidFundamentalMatrices.FluidFundamentalMatrices(Matrix Fpp, Matrix Fpm, Matrix Fmp, Matrix Fmm, Double precision_, Integer maxNumIt_, String method_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1FCFS.MMAPPH1FCFS(MatrixCell D, Map<Integer,Matrix> sigma, Map<Integer,Matrix> S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stDistr, boolean stDistrME, boolean stDistrPH, Double prec, Matrix classes_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1NPPR.MMAPPH1NPPR(MatrixCell D, MatrixCell sigma, MatrixCell S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stCdfPoints, Double prec, Integer erlMaxOrder_, Matrix classes_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1PRPR.MMAPPH1PRPR(MatrixCell D, MatrixCell sigma, MatrixCell S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stCdfPoints, Double prec, Integer erlMaxOrder_, Matrix classes_)
static Map<String,Matrix>	QBDFundamentalMatrices.QBDFundamentalMatrices(Matrix B, Matrix L, Matrix F, Double precision_, Integer maxNumIt_, String method_, Integer Verbose_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1FCFS.solve(MatrixCell D, Map<Integer,Matrix> sigma, Map<Integer,Matrix> S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stDistr, boolean stDistrME, boolean stDistrPH, Double prec, Matrix classes_)	Convenience alias for callers that expect a solve(...) entry point on the MMAPPH1FCFS class.

Methods in jline.lib.butools with parameters of type Matrix

Modifier and Type	Method	Description
static boolean	CheckMoments.checkMoments(Matrix m)
static boolean	CheckMoments.checkMoments(Matrix m, double prec)	Checks if the given moment sequence is valid in the sense that it belongs to a distribution with support (0,inf).
static Matrix	FactorialMomsFromMoms.factorialMomsFromMoms(Matrix m)	Returns the factorial moments given the raw moments.
static Map<String,Matrix>	FluidFundamentalMatrices.FluidFundamentalMatrices(Matrix Fpp, Matrix Fpm, Matrix Fmp, Matrix Fmm, Double precision_, Integer maxNumIt_, String method_)
static Matrix	HankelMomsFromMoms.hankelMomsFromMoms(Matrix m)	Returns the Hankel moments given the raw moments.
static Matrix	JFactorialMomsFromJMoms.jFactorialMomsFromJMoms(Matrix jm)	Returns the lag-1 joint factorial moments given the lag-1 joint raw moments.
static Matrix	JMomsFromJFactorialMoms.jMomsFromJFactorialMoms(Matrix jfm)	Returns the lag-1 joint raw moments given the lag-1 joint factorial moments.
static Map<String,Map<Integer,Matrix>>	MMAPPH1FCFS.MMAPPH1FCFS(MatrixCell D, Map<Integer,Matrix> sigma, Map<Integer,Matrix> S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stDistr, boolean stDistrME, boolean stDistrPH, Double prec, Matrix classes_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1NPPR.MMAPPH1NPPR(MatrixCell D, MatrixCell sigma, MatrixCell S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stCdfPoints, Double prec, Integer erlMaxOrder_, Matrix classes_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1PRPR.MMAPPH1PRPR(MatrixCell D, MatrixCell sigma, MatrixCell S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stCdfPoints, Double prec, Integer erlMaxOrder_, Matrix classes_)
static Matrix	MomsFromFactorialMoms.MomsFromFactorialMoms(Matrix fm)	Returns the raw moments given the factorial moments.
static Matrix	MomsFromHankelMoms.momsFromHankelMoms(Matrix hm)	Returns the raw moments given the Hankel moments.
static Matrix	MomsFromNormMoms.momsFromNormMoms(Matrix nm)	Returns the raw moments given the normalized moments.
static Matrix	MomsFromReducedMoms.momsFromReducedMoms(Matrix rm)	Returns the raw moments given the reduced moments.
static Matrix	Poly.poly(Matrix x)
static Map<String,Matrix>	QBDFundamentalMatrices.QBDFundamentalMatrices(Matrix B, Matrix L, Matrix F, Double precision_, Integer maxNumIt_, String method_, Integer Verbose_)
static Matrix	ReducedMomsFromMoms.reducedMomsFromMoms(Matrix m)	Returns the reduced moments given the raw moments.
static Matrix	SimilarityMatrixForVectors.SimilarityMatrixForVectors(Matrix vecA, Matrix vecB)
static Map<String,Map<Integer,Matrix>>	MMAPPH1FCFS.solve(MatrixCell D, Map<Integer,Matrix> sigma, Map<Integer,Matrix> S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stDistr, boolean stDistrME, boolean stDistrPH, Double prec, Matrix classes_)	Convenience alias for callers that expect a solve(...) entry point on the MMAPPH1FCFS class.

Method parameters in jline.lib.butools with type arguments of type Matrix

Modifier and Type	Method	Description
static Map<String,Map<Integer,Matrix>>	MMAPPH1FCFS.MMAPPH1FCFS(MatrixCell D, Map<Integer,Matrix> sigma, Map<Integer,Matrix> S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stDistr, boolean stDistrME, boolean stDistrPH, Double prec, Matrix classes_)
static Map<String,Map<Integer,Matrix>>	MMAPPH1FCFS.solve(MatrixCell D, Map<Integer,Matrix> sigma, Map<Integer,Matrix> S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stDistr, boolean stDistrME, boolean stDistrPH, Double prec, Matrix classes_)	Convenience alias for callers that expect a solve(...) entry point on the MMAPPH1FCFS class.

Uses of Matrix in jline.lib.butools.dmap

Methods in jline.lib.butools.dmap that return Matrix

Modifier and Type	Method	Description
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1)
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1, int K)
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1, int K, int L)
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1, int K, int L, double prec)	Returns the lag-L joint moments of a discrete Markovian arrival process.
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1, int K)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1, int K, int L)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1, int K, int L, double prec)	Returns the lag-L joint moments of a discrete rational arrival process.

Methods in jline.lib.butools.dmap that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	CanonicalFromDMAP2.canonicalFromDMAP2(Matrix D0, Matrix D1)
static Pair<Matrix,Matrix>	CanonicalFromDMAP2.canonicalFromDMAP2(Matrix D0, Matrix D1)
static Pair<Matrix,Matrix>	CanonicalFromDMAP2.canonicalFromDMAP2(Matrix D0, Matrix D1, double prec)	Returns the canonical form of an order-2 discrete Markovian arrival process.
static Pair<Matrix,Matrix>	CanonicalFromDMAP2.canonicalFromDMAP2(Matrix D0, Matrix D1, double prec)	Returns the canonical form of an order-2 discrete Markovian arrival process.
static Pair<Matrix,Matrix>	DMAP2FromMoments.dmap2FromMoments(double[] moms, double corr1)	Returns a discrete MAP(2) which has the same 3 marginal moments and lag-1 autocorrelation as given.
static Pair<Matrix,Matrix>	DMAP2FromMoments.dmap2FromMoments(double[] moms, double corr1)	Returns a discrete MAP(2) which has the same 3 marginal moments and lag-1 autocorrelation as given.
static Pair<Matrix,Matrix>	DMAPFromDRAP.dmapFromDRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	DMAPFromDRAP.dmapFromDRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	DMAPFromDRAP.dmapFromDRAP(Matrix H0, Matrix H1, double prec)	Obtains a Markovian representation of a discrete rational arrival process of the same size, if possible.
static Pair<Matrix,Matrix>	DMAPFromDRAP.dmapFromDRAP(Matrix H0, Matrix H1, double prec)	Obtains a Markovian representation of a discrete rational arrival process of the same size, if possible.
static Pair<Matrix,Matrix>	DRAPFromMoments.drapFromMoments(double[] moms, Matrix Nm)	Creates a discrete rational arrival process that has the same marginal and lag-1 joint moments as given.
static Pair<Matrix,Matrix>	DRAPFromMoments.drapFromMoments(double[] moms, Matrix Nm)	Creates a discrete rational arrival process that has the same marginal and lag-1 joint moments as given.
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries, int maxTrials)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries, int maxTrials)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries, int maxTrials, double prec)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries, int maxTrials, double prec)
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries, int maxTrials, double prec, Random random)	Returns a random discrete Markovian arrival process.
static Pair<Matrix,Matrix>	RandomDMAP.randomDMAP(int order, double mean, int zeroEntries, int maxTrials, double prec, Random random)	Returns a random discrete Markovian arrival process.

Methods in jline.lib.butools.dmap with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	CanonicalFromDMAP2.canonicalFromDMAP2(Matrix D0, Matrix D1)
static Pair<Matrix,Matrix>	CanonicalFromDMAP2.canonicalFromDMAP2(Matrix D0, Matrix D1, double prec)	Returns the canonical form of an order-2 discrete Markovian arrival process.
static boolean	CheckDMAPRepresentation.checkDMAPRepresentation(Matrix D0, Matrix D1)
static boolean	CheckDMAPRepresentation.checkDMAPRepresentation(Matrix D0, Matrix D1, double prec)	Checks if the input matrices define a discrete time MAP.
static boolean	CheckDMMAPRepresentation.checkDMMAPRepresentation(Matrix[] D)
static boolean	CheckDMMAPRepresentation.checkDMMAPRepresentation(Matrix[] D, double prec)	Overload for Matrix[].
static boolean	CheckDMRAPRepresentation.checkDMRAPRepresentation(Matrix[] H)
static boolean	CheckDMRAPRepresentation.checkDMRAPRepresentation(Matrix[] H, double prec)	Overload for Matrix[].
static boolean	CheckDRAPRepresentation.checkDRAPRepresentation(Matrix D0, Matrix D1)
static boolean	CheckDRAPRepresentation.checkDRAPRepresentation(Matrix D0, Matrix D1, double prec)	Checks if the input matrices define a discrete time RAP.
static Pair<Matrix,Matrix>	DMAPFromDRAP.dmapFromDRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	DMAPFromDRAP.dmapFromDRAP(Matrix H0, Matrix H1, double prec)	Obtains a Markovian representation of a discrete rational arrival process of the same size, if possible.
static MatrixCell	DMMAPFromDMRAP.dmmapFromDMRAP(Matrix[] H)
static MatrixCell	DMMAPFromDMRAP.dmmapFromDMRAP(Matrix[] H, double prec)
static MatrixCell	DMRAPFromMoments.dmrapFromMoments(double[] moms, Matrix[] Nm)
static Pair<Matrix,Matrix>	DRAPFromMoments.drapFromMoments(double[] moms, Matrix Nm)	Creates a discrete rational arrival process that has the same marginal and lag-1 joint moments as given.
static double[]	LagCorrelationsFromDMAP.lagCorrelationsFromDMAP(Matrix D0, Matrix D1)
static double[]	LagCorrelationsFromDMAP.lagCorrelationsFromDMAP(Matrix D0, Matrix D1, int L)
static double[]	LagCorrelationsFromDMAP.lagCorrelationsFromDMAP(Matrix D0, Matrix D1, int L, double prec)	Returns the lag autocorrelations of a discrete Markovian arrival process.
static double[]	LagCorrelationsFromDRAP.lagCorrelationsFromDRAP(Matrix H0, Matrix H1)
static double[]	LagCorrelationsFromDRAP.lagCorrelationsFromDRAP(Matrix H0, Matrix H1, int L)
static double[]	LagCorrelationsFromDRAP.lagCorrelationsFromDRAP(Matrix H0, Matrix H1, int L, double prec)	Returns the lag autocorrelations of a discrete rational arrival process.
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1)
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1, int K)
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1, int K, int L)
static Matrix	LagkJointMomentsFromDMAP.lagkJointMomentsFromDMAP(Matrix D0, Matrix D1, int K, int L, double prec)	Returns the lag-L joint moments of a discrete Markovian arrival process.
static MatrixCell	LagkJointMomentsFromDMMAP.lagkJointMomentsFromDMMAP(Matrix[] D)
static MatrixCell	LagkJointMomentsFromDMMAP.lagkJointMomentsFromDMMAP(Matrix[] D, int K)
static MatrixCell	LagkJointMomentsFromDMMAP.lagkJointMomentsFromDMMAP(Matrix[] D, int K, int L)
static MatrixCell	LagkJointMomentsFromDMMAP.lagkJointMomentsFromDMMAP(Matrix[] D, int K, int L, double prec)	Overload for Matrix[].
static MatrixCell	LagkJointMomentsFromDMRAP.lagkJointMomentsFromDMRAP(Matrix[] H)
static MatrixCell	LagkJointMomentsFromDMRAP.lagkJointMomentsFromDMRAP(Matrix[] H, int K)
static MatrixCell	LagkJointMomentsFromDMRAP.lagkJointMomentsFromDMRAP(Matrix[] H, int K, int L)
static MatrixCell	LagkJointMomentsFromDMRAP.lagkJointMomentsFromDMRAP(Matrix[] H, int K, int L, double prec)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1, int K)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1, int K, int L)
static Matrix	LagkJointMomentsFromDRAP.lagkJointMomentsFromDRAP(Matrix H0, Matrix H1, int K, int L, double prec)	Returns the lag-L joint moments of a discrete rational arrival process.
static MGFromMoments.MGRepresentation	MarginalDistributionFromDMAP.marginalDistributionFromDMAP(Matrix D0, Matrix D1)
static MGFromMoments.MGRepresentation	MarginalDistributionFromDMAP.marginalDistributionFromDMAP(Matrix D0, Matrix D1, double prec)	Returns the discrete phase type distributed marginal distribution of a discrete Markovian arrival process.
static MGFromMoments.MGRepresentation	MarginalDistributionFromDMMAP.marginalDistributionFromDMMAP(Matrix[] D)
static MGFromMoments.MGRepresentation	MarginalDistributionFromDMMAP.marginalDistributionFromDMMAP(Matrix[] D, double prec)
static MGFromMoments.MGRepresentation	MarginalDistributionFromDMRAP.marginalDistributionFromDMRAP(Matrix[] H)
static MGFromMoments.MGRepresentation	MarginalDistributionFromDMRAP.marginalDistributionFromDMRAP(Matrix[] H, double prec)	Overload for Matrix[].
static MGFromMoments.MGRepresentation	MarginalDistributionFromDRAP.marginalDistributionFromDRAP(Matrix H0, Matrix H1)
static MGFromMoments.MGRepresentation	MarginalDistributionFromDRAP.marginalDistributionFromDRAP(Matrix H0, Matrix H1, double prec)	Returns the matrix geometrically distributed marginal distribution of a discrete rational arrival process.
static double[]	MarginalMomentsFromDMAP.marginalMomentsFromDMAP(Matrix D0, Matrix D1)
static double[]	MarginalMomentsFromDMAP.marginalMomentsFromDMAP(Matrix D0, Matrix D1, int K)
static double[]	MarginalMomentsFromDMAP.marginalMomentsFromDMAP(Matrix D0, Matrix D1, int K, double prec)	Returns the moments of the marginal distribution of a discrete Markovian arrival process.
static double[]	MarginalMomentsFromDMMAP.marginalMomentsFromDMMAP(Matrix[] D)
static double[]	MarginalMomentsFromDMMAP.marginalMomentsFromDMMAP(Matrix[] D, int K)
static double[]	MarginalMomentsFromDMMAP.marginalMomentsFromDMMAP(Matrix[] D, int K, double prec)	Overload for Matrix[].
static double[]	MarginalMomentsFromDMRAP.marginalMomentsFromDMRAP(Matrix[] H)
static double[]	MarginalMomentsFromDMRAP.marginalMomentsFromDMRAP(Matrix[] H, int K)
static double[]	MarginalMomentsFromDMRAP.marginalMomentsFromDMRAP(Matrix[] H, int K, double prec)	Overload for Matrix[].
static double[]	MarginalMomentsFromDRAP.marginalMomentsFromDRAP(Matrix H0, Matrix H1)
static double[]	MarginalMomentsFromDRAP.marginalMomentsFromDRAP(Matrix H0, Matrix H1, int K)
static double[]	MarginalMomentsFromDRAP.marginalMomentsFromDRAP(Matrix H0, Matrix H1, int K, double prec)	Returns the moments of the marginal distribution of a discrete rational arrival process.
static int[]	SamplesFromDMAP.samplesFromDMAP(Matrix D0, Matrix D1, int K)
static int[]	SamplesFromDMAP.samplesFromDMAP(Matrix D0, Matrix D1, int K, Integer initial)
static int[]	SamplesFromDMAP.samplesFromDMAP(Matrix D0, Matrix D1, int K, Integer initial, double prec)
static int[]	SamplesFromDMAP.samplesFromDMAP(Matrix D0, Matrix D1, int K, Integer initial, double prec, Random random)	Generates random samples from a discrete Markovian arrival process.
static Object	SamplesFromDMMAP.samplesFromDMMAP(Matrix[] D, int K)
static Object	SamplesFromDMMAP.samplesFromDMMAP(Matrix[] D, int K, Integer initial, double prec, Random random)

Uses of Matrix in jline.lib.butools.dph

Fields in jline.lib.butools.dph declared as Matrix

Modifier and Type	Field	Description
final Matrix	MGFromMoments.MGRepresentation.A
final Matrix	MGFromMoments.MGRepresentation.alpha
final Matrix	CanonicalFromDPH2.DPH2Representation.B
final Matrix	CanonicalFromDPH3.DPH3Representation.B
final Matrix	CanonicalFromDPH2.DPH2Representation.beta
final Matrix	CanonicalFromDPH3.DPH3Representation.beta

Methods in jline.lib.butools.dph that return Matrix

Modifier and Type	Method	Description
Matrix	CanonicalFromDPH2.DPH2Representation.component1()
Matrix	MGFromMoments.MGRepresentation.component1()
Matrix	CanonicalFromDPH2.DPH2Representation.component2()
Matrix	MGFromMoments.MGRepresentation.component2()
Matrix	MGFromMoments.MGRepresentation.getA()
Matrix	MGFromMoments.MGRepresentation.getAlpha()

Methods in jline.lib.butools.dph with parameters of type Matrix

Modifier and Type	Method	Description
static MGFromMoments.MGRepresentation	AcyclicDPHFromMG.acyclicDPHFromMG(double[] alpha, Matrix A)
static MGFromMoments.MGRepresentation	AcyclicDPHFromMG.acyclicDPHFromMG(double[] alpha, Matrix A, double prec)
static MGFromMoments.MGRepresentation	AcyclicDPHFromMG.acyclicDPHFromMG(Matrix alpha, Matrix A)
static MGFromMoments.MGRepresentation	AcyclicDPHFromMG.acyclicDPHFromMG(Matrix alpha, Matrix A, double prec)	Transforms a matrix-geometric representation to an acyclic DPH representation of the same size, if possible.
static CanonicalFromDPH2.DPH2Representation	CanonicalFromDPH2.canonicalFromDPH2(double[] alpha, Matrix A)
static CanonicalFromDPH2.DPH2Representation	CanonicalFromDPH2.canonicalFromDPH2(double[] alpha, Matrix A, double prec)	Overload for double[] alpha.
static CanonicalFromDPH2.DPH2Representation	CanonicalFromDPH2.canonicalFromDPH2(Matrix alpha, Matrix A)
static CanonicalFromDPH2.DPH2Representation	CanonicalFromDPH2.canonicalFromDPH2(Matrix alpha, Matrix A, double prec)
static CanonicalFromDPH3.DPH3Representation	CanonicalFromDPH3.canonicalFromDPH3(double[] alpha, Matrix A)
static CanonicalFromDPH3.DPH3Representation	CanonicalFromDPH3.canonicalFromDPH3(double[] alpha, Matrix A, double prec)
static CanonicalFromDPH3.DPH3Representation	CanonicalFromDPH3.canonicalFromDPH3(Matrix alpha, Matrix A)
static CanonicalFromDPH3.DPH3Representation	CanonicalFromDPH3.canonicalFromDPH3(Matrix alpha, Matrix A, double prec)
static double	CdfFromDPH.cdfFromDPH(double[] alpha, Matrix A, int x)	Overload for double[] alpha and single integer x.
static double[]	CdfFromDPH.cdfFromDPH(double[] alpha, Matrix A, int[] x)	Overload for double[] alpha.
static double	CdfFromDPH.cdfFromDPH(Matrix alpha, Matrix A, int x)	Overload for single integer x.
static double[]	CdfFromDPH.cdfFromDPH(Matrix alpha, Matrix A, int[] x)	Returns the cumulative distribution function of a discrete phase-type distribution.
static double	CdfFromMG.cdfFromMG(double[] alpha, Matrix A, int x)	Overload for double[] alpha and single integer x.
static double[]	CdfFromMG.cdfFromMG(double[] alpha, Matrix A, int[] x)	Overload for double[] alpha.
static double	CdfFromMG.cdfFromMG(Matrix alpha, Matrix A, int x)	Overload for single integer x.
static double[]	CdfFromMG.cdfFromMG(Matrix alpha, Matrix A, int[] x)	Returns the cumulative distribution function of a matrix-geometric distribution.
static boolean	CheckDPHRepresentation.checkDPHRepresentation(double[] alpha, Matrix A)
static boolean	CheckDPHRepresentation.checkDPHRepresentation(double[] alpha, Matrix A, double prec)	Overload for double[] alpha.
static boolean	CheckDPHRepresentation.checkDPHRepresentation(Matrix alpha, Matrix A)
static boolean	CheckDPHRepresentation.checkDPHRepresentation(Matrix alpha, Matrix A, double prec)	Checks if the given vector and matrix define a valid discrete phase-type representation.
static boolean	CheckMGRepresentation.checkMGRepresentation(double[] alpha, Matrix A)
static boolean	CheckMGRepresentation.checkMGRepresentation(double[] alpha, Matrix A, double prec)
static boolean	CheckMGRepresentation.checkMGRepresentation(Matrix alpha, Matrix A)
static boolean	CheckMGRepresentation.checkMGRepresentation(Matrix alpha, Matrix A, double prec)	Checks if the given vector and matrix define a valid matrix-geometric representation.
static MGFromMoments.MGRepresentation	DPHFromMG.dphFromMG(double[] alpha, Matrix A)
static MGFromMoments.MGRepresentation	DPHFromMG.dphFromMG(double[] alpha, Matrix A, double precision)	Overload for double[] alpha.
static MGFromMoments.MGRepresentation	DPHFromMG.dphFromMG(Matrix alpha, Matrix A)
static MGFromMoments.MGRepresentation	DPHFromMG.dphFromMG(Matrix alpha, Matrix A, double precision)	Obtains a Markovian representation of a matrix-geometric distribution of the same size, if possible.
static double[]	MomentsFromDPH.momentsFromDPH(double[] alpha, Matrix A)
static double[]	MomentsFromDPH.momentsFromDPH(double[] alpha, Matrix A, int K)	Overload for double[] alpha.
static double[]	MomentsFromDPH.momentsFromDPH(Matrix alpha, Matrix A)
static double[]	MomentsFromDPH.momentsFromDPH(Matrix alpha, Matrix A, int K)	Returns the first K moments of a discrete phase-type distribution.
static double[]	MomentsFromMG.momentsFromMG(double[] alpha, Matrix A)
static double[]	MomentsFromMG.momentsFromMG(double[] alpha, Matrix A, int K)
static double[]	MomentsFromMG.momentsFromMG(Matrix alpha, Matrix A)
static double[]	MomentsFromMG.momentsFromMG(Matrix alpha, Matrix A, int K)	Returns the first K moments of a matrix-geometric distribution.
static double	PmfFromDPH.pmfFromDPH(double[] alpha, Matrix A, int x)	Overload for double[] alpha and single integer x.
static double[]	PmfFromDPH.pmfFromDPH(double[] alpha, Matrix A, int[] x)	Overload for double[] alpha.
static double	PmfFromDPH.pmfFromDPH(Matrix alpha, Matrix A, int x)	Overload for single integer x.
static double[]	PmfFromDPH.pmfFromDPH(Matrix alpha, Matrix A, int[] x)	Returns the probability mass function of a discrete phase-type distribution.
static double	PmfFromMG.pmfFromMG(double[] alpha, Matrix A, int x)
static double[]	PmfFromMG.pmfFromMG(double[] alpha, Matrix A, int[] x)
static double	PmfFromMG.pmfFromMG(Matrix alpha, Matrix A, int x)
static double[]	PmfFromMG.pmfFromMG(Matrix alpha, Matrix A, int[] x)	Returns the probability mass function of a matrix-geometric distribution.
static int[]	SamplesFromDPH.samplesFromDPH(double[] alpha, Matrix A, int K)
static int[]	SamplesFromDPH.samplesFromDPH(double[] alpha, Matrix A, int K, Random random)	Overload for double[] alpha.
static int[]	SamplesFromDPH.samplesFromDPH(Matrix alpha, Matrix A, int K)
static int[]	SamplesFromDPH.samplesFromDPH(Matrix alpha, Matrix A, int K, Random random)	Generates random samples from a discrete phase-type distribution.

Constructors in jline.lib.butools.dph with parameters of type Matrix

Modifier	Constructor	Description
	DPH2Representation(Matrix beta, Matrix B)
	DPH3Representation(Matrix beta, Matrix B)
	MGRepresentation(Matrix alpha, Matrix A)

Uses of Matrix in jline.lib.butools.fitting

Fields in jline.lib.butools.fitting declared as Matrix

Modifier and Type	Field	Description
final Matrix	PHFromTrace.PHFitResult.A
final Matrix	PHFromTrace.PHFitResult.alpha
final Matrix	MAPFitResult.D0
final Matrix	MAPFitResult.D1

Methods in jline.lib.butools.fitting with parameters of type Matrix

Modifier and Type	Method	Description
static double	LikelihoodFromTrace.likelihoodFromTraceMAP(double[] trace, Matrix D0, Matrix D1)
static double	LikelihoodFromTrace.likelihoodFromTraceMAP(double[] trace, Matrix D0, Matrix D1, double prec)	Evaluates the log-likelihood of a trace with the given MAP.
static double	LikelihoodFromTrace.likelihoodFromTracePH(double[] trace, Matrix alpha, Matrix A)
static double	LikelihoodFromTrace.likelihoodFromTracePH(double[] trace, Matrix alpha, Matrix A, double prec)	Evaluates the log-likelihood of a trace with the given PH distribution.
static MAPFitResult	MAPFromTrace.mapFromTrace(double[] trace, int[] orders, int maxIter, double stopCond, Matrix[] initialGuess)
static MAPFitResult	MAPFromTrace.mapFromTrace(double[] trace, int[] orders, int maxIter, double stopCond, Matrix[] initialGuess, String resultFormat)	Performs MAP fitting using the EM algorithm (ErCHMM).

Constructors in jline.lib.butools.fitting with parameters of type Matrix

Modifier	Constructor	Description
	MAPFitResult(Matrix D0, Matrix D1, double logli)
	PHFitResult(Matrix alpha, Matrix A, double logli)

Uses of Matrix in jline.lib.butools.mam

Fields in jline.lib.butools.mam declared as Matrix

Modifier and Type	Field	Description
final Matrix	FluidSolve.FluidSolution.clo
final Matrix	FluidSolve.FluidSolution.ini
final Matrix	FluidSolve.FluidSolution.K
final Matrix	FluidSolve.FluidSolution.mass0

Methods in jline.lib.butools.mam that return Matrix

Modifier and Type	Method	Description
static Matrix	FluidStationaryDistr.fluidStationaryDistr(Matrix mass0, Matrix ini, Matrix K, Matrix clo, double[] x)	Returns the stationary distribution of a Markovian fluid model at specific points.
Matrix	GeneralFluidSolution.getClo()
Matrix	GeneralFluidSolution.getIni()
Matrix	GeneralFluidSolution.getK()
Matrix	GeneralFluidSolution.getMass0()
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A)
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A, double precision)
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt)
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt, GM1FundamentalMatrix.GM1Method method)	Returns matrix R corresponding to the G/M/1 type Markov chain given by matrices A.
static Matrix	GM1StationaryDistr.gm1StationaryDistr(List<Matrix> B, Matrix R, int K)	Returns the stationary distribution of the G/M/1 type Markov chain up to a given level K.
static Matrix	GM1StationaryDistr.gm1StationaryDistr(Matrix[] B, Matrix R, int K)	Overload accepting Matrix[].
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A)
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A, double precision)
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt)
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt, MG1FundamentalMatrix.MG1Method method)	Returns matrix G corresponding to the M/G/1 type Markov chain defined by matrices A.
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G, int K)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G, int K, double prec)	Returns the stationary distribution of the M/G/1 type Markov chain up to a given level K.
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B, Matrix G)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B, Matrix G, int K)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B, Matrix G, int K, double prec)	Overload accepting Matrix[] for A and B.
static Matrix	QBDStationaryDistr.qbdStationaryDistr(double[] pi0, Matrix R, int K)	Overload for double[] pi0.
static Matrix	QBDStationaryDistr.qbdStationaryDistr(Matrix pi0, Matrix R, int K)	Returns the stationary distribution of a QBD up to a given level K.

Methods in jline.lib.butools.mam that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	QBDSolve.qbdSolve(Matrix B, Matrix L, Matrix F, Matrix L0)
static Pair<Matrix,Matrix>	QBDSolve.qbdSolve(Matrix B, Matrix L, Matrix F, Matrix L0)
static Pair<Matrix,Matrix>	QBDSolve.qbdSolve(Matrix B, Matrix L, Matrix F, Matrix L0, double prec)	Returns the parameters of the matrix-geometrically distributed stationary distribution of a QBD.
static Pair<Matrix,Matrix>	QBDSolve.qbdSolve(Matrix B, Matrix L, Matrix F, Matrix L0, double prec)	Returns the parameters of the matrix-geometrically distributed stationary distribution of a QBD.

Methods in jline.lib.butools.mam with parameters of type Matrix

Modifier and Type	Method	Description
static FluidSolve.FluidSolution	FluidSolve.fluidSolve(Matrix Fpp, Matrix Fpm, Matrix Fmp, Matrix Fmm)
static FluidSolve.FluidSolution	FluidSolve.fluidSolve(Matrix Fpp, Matrix Fpm, Matrix Fmp, Matrix Fmm, double prec)	Returns the parameters of the matrix-exponentially distributed stationary distribution of a canonical Markovian fluid model.
static Matrix	FluidStationaryDistr.fluidStationaryDistr(Matrix mass0, Matrix ini, Matrix K, Matrix clo, double[] x)	Returns the stationary distribution of a Markovian fluid model at specific points.
static GeneralFluidSolution	GeneralFluidSolve.generalFluidSolve(Matrix Q, Matrix R)
static GeneralFluidSolution	GeneralFluidSolve.generalFluidSolve(Matrix Q, Matrix R, Matrix Q0)
static GeneralFluidSolution	GeneralFluidSolve.generalFluidSolve(Matrix Q, Matrix R, Matrix Q0, double prec)	Returns the parameters of the matrix-exponentially distributed stationary distribution of a general Markovian fluid model.
static Matrix	GM1StationaryDistr.gm1StationaryDistr(List<Matrix> B, Matrix R, int K)	Returns the stationary distribution of the G/M/1 type Markov chain up to a given level K.
static Matrix	GM1StationaryDistr.gm1StationaryDistr(Matrix[] B, Matrix R, int K)	Overload accepting Matrix[].
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G, int K)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G, int K, double prec)	Returns the stationary distribution of the M/G/1 type Markov chain up to a given level K.
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B, Matrix G)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B, Matrix G, int K)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(Matrix[] A, Matrix[] B, Matrix G, int K, double prec)	Overload accepting Matrix[] for A and B.
static Pair<Matrix,Matrix>	QBDSolve.qbdSolve(Matrix B, Matrix L, Matrix F, Matrix L0)
static Pair<Matrix,Matrix>	QBDSolve.qbdSolve(Matrix B, Matrix L, Matrix F, Matrix L0, double prec)	Returns the parameters of the matrix-geometrically distributed stationary distribution of a QBD.
static Matrix	QBDStationaryDistr.qbdStationaryDistr(double[] pi0, Matrix R, int K)	Overload for double[] pi0.
static Matrix	QBDStationaryDistr.qbdStationaryDistr(Matrix pi0, Matrix R, int K)	Returns the stationary distribution of a QBD up to a given level K.

Method parameters in jline.lib.butools.mam with type arguments of type Matrix

Modifier and Type	Method	Description
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A)
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A, double precision)
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt)
static Matrix	GM1FundamentalMatrix.gm1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt, GM1FundamentalMatrix.GM1Method method)	Returns matrix R corresponding to the G/M/1 type Markov chain given by matrices A.
static Matrix	GM1StationaryDistr.gm1StationaryDistr(List<Matrix> B, Matrix R, int K)	Returns the stationary distribution of the G/M/1 type Markov chain up to a given level K.
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A)
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A, double precision)
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt)
static Matrix	MG1FundamentalMatrix.mg1FundamentalMatrix(List<Matrix> A, double precision, int maxNumIt, MG1FundamentalMatrix.MG1Method method)	Returns matrix G corresponding to the M/G/1 type Markov chain defined by matrices A.
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G, int K)
static Matrix	MG1StationaryDistr.mg1StationaryDistr(List<Matrix> A, List<Matrix> B, Matrix G, int K, double prec)	Returns the stationary distribution of the M/G/1 type Markov chain up to a given level K.

Constructors in jline.lib.butools.mam with parameters of type Matrix

Modifier	Constructor	Description
	FluidSolution(Matrix mass0, Matrix ini, Matrix K, Matrix clo)
	GeneralFluidSolution(Matrix mass0, Matrix ini, Matrix K, Matrix clo)

Uses of Matrix in jline.lib.butools.map

Methods in jline.lib.butools.map that return Matrix

Modifier and Type	Method	Description
Matrix	MAPRepresentation.component1()
Matrix	MAPRepresentation.component2()
Matrix	MAPRepresentation.getD0()
Matrix	MAPRepresentation.getD1()
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1)
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1, int K)
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1, int K, int L)
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1, int K, int L, double prec)	Returns the lag-L joint moments of a continuous Markovian arrival process.
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1)
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1, int K)
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1, int K, int L)
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1, int K, int L, double prec)	Returns the lag-L joint moments of a continuous rational arrival process.
static Matrix[]	MAPFromFewMomentsAndCorrelations.mapFromFewMomentsAndCorrelations(double[] moms)
static Matrix[]	MAPFromFewMomentsAndCorrelations.mapFromFewMomentsAndCorrelations(double[] moms, double corr1)
static Matrix[]	MAPFromFewMomentsAndCorrelations.mapFromFewMomentsAndCorrelations(double[] moms, double corr1, Double r)	Creates a Markovian arrival process that has the given 2 or 3 marginal moments and lag-1 autocorrelation.

Methods in jline.lib.butools.map that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	CanonicalFromMAP2.canonicalFromMAP2(Matrix D0, Matrix D1)
static Pair<Matrix,Matrix>	CanonicalFromMAP2.canonicalFromMAP2(Matrix D0, Matrix D1)
static Pair<Matrix,Matrix>	CanonicalFromMAP2.canonicalFromMAP2(Matrix D0, Matrix D1, double prec)	Returns the canonical form of an order-2 Markovian arrival process.
static Pair<Matrix,Matrix>	CanonicalFromMAP2.canonicalFromMAP2(Matrix D0, Matrix D1, double prec)	Returns the canonical form of an order-2 Markovian arrival process.
static Pair<Matrix,Matrix>	MAP2FromMoments.map2FromMoments(double[] moms, double corr1)	Returns a MAP(2) which has the same 3 marginal moments and lag-1 autocorrelation as given.
static Pair<Matrix,Matrix>	MAP2FromMoments.map2FromMoments(double[] moms, double corr1)	Returns a MAP(2) which has the same 3 marginal moments and lag-1 autocorrelation as given.
static Pair<Matrix,Matrix>	MAPFromRAP.mapFromRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	MAPFromRAP.mapFromRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	MAPFromRAP.mapFromRAP(Matrix H0, Matrix H1, double prec)	Obtains a Markovian representation of a continuous rational arrival process of the same size, if possible.
static Pair<Matrix,Matrix>	MAPFromRAP.mapFromRAP(Matrix H0, Matrix H1, double prec)	Obtains a Markovian representation of a continuous rational arrival process of the same size, if possible.
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1, String how)
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1, String how)
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1, String how, double precision)	Returns the minimal representation of a rational arrival process.
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1, String how, double precision)	Returns the minimal representation of a rational arrival process.
static Pair<Matrix,Matrix>	MRAPFromMoments.rapFromMoments(double[] moms, Matrix Nm)	Creates a rational arrival process that has the same marginal and lag-1 joint moments as given.
static Pair<Matrix,Matrix>	MRAPFromMoments.rapFromMoments(double[] moms, Matrix Nm)	Creates a rational arrival process that has the same marginal and lag-1 joint moments as given.
static Pair<Matrix,Matrix>	RAPFromMomentsAndCorrelations.rapFromMomentsAndCorrelations(double[] moms, double[] corr)	Returns a rational arrival process that has the same moments and lag autocorrelation coefficients as given.
static Pair<Matrix,Matrix>	RAPFromMomentsAndCorrelations.rapFromMomentsAndCorrelations(double[] moms, double[] corr)	Returns a rational arrival process that has the same moments and lag autocorrelation coefficients as given.

Methods in jline.lib.butools.map with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	CanonicalFromMAP2.canonicalFromMAP2(Matrix D0, Matrix D1)
static Pair<Matrix,Matrix>	CanonicalFromMAP2.canonicalFromMAP2(Matrix D0, Matrix D1, double prec)	Returns the canonical form of an order-2 Markovian arrival process.
static boolean	CheckMAPRepresentation.checkMAPRepresentation(Matrix D0, Matrix D1)
static boolean	CheckMAPRepresentation.checkMAPRepresentation(Matrix D0, Matrix D1, double prec)	Checks if the input matrices define a continuous time MAP.
static boolean	CheckMMAPRepresentation.checkMMAPRepresentation(Matrix[] D)
static boolean	CheckMMAPRepresentation.checkMMAPRepresentation(Matrix[] D, double prec)	Overload for Matrix[].
static boolean	CheckMRAPRepresentation.checkMRAPRepresentation(Matrix[] H)
static boolean	CheckMRAPRepresentation.checkMRAPRepresentation(Matrix[] H, double prec)	Overload for Matrix[].
static boolean	CheckMAPRepresentation.checkRAPRepresentation(Matrix H0, Matrix H1)
static boolean	CheckMAPRepresentation.checkRAPRepresentation(Matrix H0, Matrix H1, double prec)	Checks if the input matrices define a valid RAP representation.
static double[]	LagCorrelationsFromMAP.lagCorrelationsFromMAP(Matrix D0, Matrix D1)
static double[]	LagCorrelationsFromMAP.lagCorrelationsFromMAP(Matrix D0, Matrix D1, int L)	Returns the lag autocorrelations of a Markovian arrival process.
static double[]	LagCorrelationsFromMAP.lagCorrelationsFromRAP(Matrix H0, Matrix H1)
static double[]	LagCorrelationsFromMAP.lagCorrelationsFromRAP(Matrix H0, Matrix H1, int L)	Returns the lag autocorrelations of a rational arrival process.
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1)
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1, int K)
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1, int K, int L)
static Matrix	LagkJointMomentsFromMAP.lagkJointMomentsFromMAP(Matrix D0, Matrix D1, int K, int L, double prec)	Returns the lag-L joint moments of a continuous Markovian arrival process.
static MatrixCell	LagkJointMomentsFromMMAP.lagkJointMomentsFromMMAP(Matrix[] D)
static MatrixCell	LagkJointMomentsFromMMAP.lagkJointMomentsFromMMAP(Matrix[] D, int K)
static MatrixCell	LagkJointMomentsFromMMAP.lagkJointMomentsFromMMAP(Matrix[] D, int K, int L)
static MatrixCell	LagkJointMomentsFromMMAP.lagkJointMomentsFromMMAP(Matrix[] D, int K, int L, double prec)	Overload for Matrix[].
static MatrixCell	LagkJointMomentsFromMRAP.lagkJointMomentsFromMRAP(Matrix[] H, int K, int L, double prec)	Overload for Matrix[].
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1)
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1, int K)
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1, int K, int L)
static Matrix	LagkJointMomentsFromRAP.lagkJointMomentsFromRAP(Matrix H0, Matrix H1, int K, int L, double prec)	Returns the lag-L joint moments of a continuous rational arrival process.
static Pair<Matrix,Matrix>	MAPFromRAP.mapFromRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	MAPFromRAP.mapFromRAP(Matrix H0, Matrix H1, double prec)	Obtains a Markovian representation of a continuous rational arrival process of the same size, if possible.
static PHRepresentation	MarginalDistributionFromMAP.marginalDistributionFromMAP(Matrix D0, Matrix D1)	Returns the phase type distributed marginal distribution of a Markovian arrival process.
static PHRepresentation	MarginalDistributionFromMMAP.marginalDistributionFromMMAP(Matrix[] D)
static PHRepresentation	MarginalDistributionFromMMAP.marginalDistributionFromMMAP(Matrix[] D, double prec)
static PHRepresentation	MarginalDistributionFromMRAP.marginalDistributionFromMRAP(Matrix[] H)
static PHRepresentation	MarginalDistributionFromMRAP.marginalDistributionFromMRAP(Matrix[] H, double prec)	Overload for Matrix[].
static PHRepresentation	MarginalDistributionFromMAP.marginalDistributionFromRAP(Matrix H0, Matrix H1)	Returns the matrix exponential distributed marginal distribution of a rational arrival process.
static double[]	MarginalMomentsFromMAP.marginalMomentsFromMAP(Matrix D0, Matrix D1)
static double[]	MarginalMomentsFromMAP.marginalMomentsFromMAP(Matrix D0, Matrix D1, int K)	Returns the moments of the marginal distribution of a Markovian arrival process.
static double[]	MarginalMomentsFromMMAP.marginalMomentsFromMMAP(Matrix[] D)
static double[]	MarginalMomentsFromMMAP.marginalMomentsFromMMAP(Matrix[] D, int K)
static double[]	MarginalMomentsFromMMAP.marginalMomentsFromMMAP(Matrix[] D, int K, double prec)	Overload for Matrix[].
static double[]	MarginalMomentsFromMRAP.marginalMomentsFromMRAP(Matrix[] H)
static double[]	MarginalMomentsFromMRAP.marginalMomentsFromMRAP(Matrix[] H, int K)
static double[]	MarginalMomentsFromMRAP.marginalMomentsFromMRAP(Matrix[] H, int K, double prec)	Overload for Matrix[].
static double[]	MarginalMomentsFromMAP.marginalMomentsFromRAP(Matrix H0, Matrix H1)
static double[]	MarginalMomentsFromMAP.marginalMomentsFromRAP(Matrix H0, Matrix H1, int K)	Returns the moments of the marginal distribution of a rational arrival process.
static MatrixCell	MinimalRepFromMRAP.minimalRepFromMRAP(Matrix[] H, String how, double precision)	Overload for Matrix[].
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1)
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1, String how)
static Pair<Matrix,Matrix>	MinimalRepFromRAP.minimalRepFromRAP(Matrix H0, Matrix H1, String how, double precision)	Returns the minimal representation of a rational arrival process.
static MatrixCell	MMAPFromMRAP.mmapFromMRAP(Matrix[] H)
static MatrixCell	MMAPFromMRAP.mmapFromMRAP(Matrix[] H, double prec)	Overload for Matrix[].
static MatrixCell	MRAPFromMoments.mrapFromMoments(double[] moms, Matrix[] Nm)	Overload for Matrix[].
static Pair<Matrix,Matrix>	MRAPFromMoments.rapFromMoments(double[] moms, Matrix Nm)	Creates a rational arrival process that has the same marginal and lag-1 joint moments as given.
static double[]	SamplesFromMAP.samplesFromMAP(Matrix D0, Matrix D1, int K)
static double[]	SamplesFromMAP.samplesFromMAP(Matrix D0, Matrix D1, int K, Integer initial)
static double[]	SamplesFromMAP.samplesFromMAP(Matrix D0, Matrix D1, int K, Integer initial, Random random)	Generates random samples from a Markovian arrival process.
static Object	SamplesFromMMAP.samplesFromMMAP(Matrix[] D, int K)
static Object	SamplesFromMMAP.samplesFromMMAP(Matrix[] D, int K, Integer initial, double prec, Random random)

Constructors in jline.lib.butools.map with parameters of type Matrix

Modifier	Constructor	Description
	MAPRepresentation(Matrix D0, Matrix D1)

Uses of Matrix in jline.lib.butools.mc

Methods in jline.lib.butools.mc that return Matrix

Modifier and Type	Method	Description
static Matrix	CRPSolve.crpSolve(Matrix Q)
static Matrix	CRPSolve.crpSolve(Matrix Q, double prec)	Computes the stationary solution of a continuous time rational process (CRP).
static Matrix	CTMCSolve.ctmcSolve(Matrix Q)
static Matrix	CTMCSolve.ctmcSolve(Matrix Q, double prec)	Computes the stationary solution of a continuous time Markov chain.
static Matrix	CRPSolve.drpSolve(Matrix P)	Computes the stationary solution of a discrete time rational process (DRP).
static Matrix	DTMCSolve.dtmcSolve(Matrix P)
static Matrix	DTMCSolve.dtmcSolve(Matrix P, double prec)	Computes the stationary solution of a discrete time Markov chain.

Methods in jline.lib.butools.mc with parameters of type Matrix

Modifier and Type	Method	Description
static boolean	CheckGenerator.checkGenerator(Matrix Q)
static boolean	CheckGenerator.checkGenerator(Matrix Q, boolean transient_)
static boolean	CheckGenerator.checkGenerator(Matrix Q, boolean transient_, double prec)	Checks if the matrix is a valid generator matrix.
static boolean	CheckProbMatrix.checkProbMatrix(Matrix P)
static boolean	CheckProbMatrix.checkProbMatrix(Matrix P, boolean transient_)
static boolean	CheckProbMatrix.checkProbMatrix(Matrix P, boolean transient_, double prec)	Checks if the matrix is a valid probability matrix.
static boolean	CheckProbVector.checkProbVector(Matrix pi)
static boolean	CheckProbVector.checkProbVector(Matrix pi, boolean sub)
static boolean	CheckProbVector.checkProbVector(Matrix pi, boolean sub, double prec)	Checks if the vector is a valid probability vector: the vector has only non-negative elements, the sum of the vector elements is 1.
static Matrix	CRPSolve.crpSolve(Matrix Q)
static Matrix	CRPSolve.crpSolve(Matrix Q, double prec)	Computes the stationary solution of a continuous time rational process (CRP).
static Matrix	CTMCSolve.ctmcSolve(Matrix Q)
static Matrix	CTMCSolve.ctmcSolve(Matrix Q, double prec)	Computes the stationary solution of a continuous time Markov chain.
static Matrix	CRPSolve.drpSolve(Matrix P)	Computes the stationary solution of a discrete time rational process (DRP).
static Matrix	DTMCSolve.dtmcSolve(Matrix P)
static Matrix	DTMCSolve.dtmcSolve(Matrix P, double prec)	Computes the stationary solution of a discrete time Markov chain.

Uses of Matrix in jline.lib.butools.ph

Fields in jline.lib.butools.ph declared as Matrix

Modifier and Type	Field	Description
final Matrix	MERepresentation.A
final Matrix	PH2From3Moments.PH2Representation.A
final Matrix	PH3Representation.A
final Matrix	PHRepresentation.A
final Matrix	MERepresentation.alpha
final Matrix	PH2From3Moments.PH2Representation.alpha
final Matrix	PH3Representation.alpha
final Matrix	PHRepresentation.alpha

Methods in jline.lib.butools.ph that return Matrix

Modifier and Type	Method	Description
Matrix	MERepresentation.component1()
Matrix	PH2From3Moments.PH2Representation.component1()
Matrix	PH3Representation.component1()
Matrix	PHRepresentation.component1()
Matrix	MERepresentation.component2()
Matrix	PH2From3Moments.PH2Representation.component2()
Matrix	PH3Representation.component2()
Matrix	PHRepresentation.component2()
Matrix	MERepresentation.getA()
Matrix	PH3Representation.getA()
Matrix	PHRepresentation.getA()
Matrix	MERepresentation.getAlpha()
Matrix	PH3Representation.getAlpha()
Matrix	PHRepresentation.getAlpha()

Methods in jline.lib.butools.ph with parameters of type Matrix

Modifier and Type	Method	Description
static PHRepresentation	AcyclicPHFromME.acyclicPHFromME(Matrix alpha, Matrix A)
static PHRepresentation	AcyclicPHFromME.acyclicPHFromME(Matrix alpha, Matrix A, int maxSize)
static PHRepresentation	AcyclicPHFromME.acyclicPHFromME(Matrix alpha, Matrix A, int maxSize, double prec)	Transforms an arbitrary matrix-exponential representation to an acyclic phase-type representation.
static PH2From3Moments.PH2Representation	CanonicalFromPH2.canonicalFromPH2(double[] alpha, Matrix A)
static PH2From3Moments.PH2Representation	CanonicalFromPH2.canonicalFromPH2(double[] alpha, Matrix A, double prec)
static PH2From3Moments.PH2Representation	CanonicalFromPH2.canonicalFromPH2(Matrix alpha, Matrix A)
static PH2From3Moments.PH2Representation	CanonicalFromPH2.canonicalFromPH2(Matrix alpha, Matrix A, double prec)	Returns the canonical form of an order-2 phase-type distribution.
static PH3Representation	CanonicalFromPH3.canonicalFromPH3(double[] alpha, Matrix A)
static PH3Representation	CanonicalFromPH3.canonicalFromPH3(double[] alpha, Matrix A, double prec)
static PH3Representation	CanonicalFromPH3.canonicalFromPH3(Matrix alpha, Matrix A)
static PH3Representation	CanonicalFromPH3.canonicalFromPH3(Matrix alpha, Matrix A, double prec)	Returns the canonical form of an order-3 phase-type distribution.
static double[]	CdfFromME.cdfFromME(double[] alpha, Matrix A, double[] x)	Overload for double[] alpha.
static double[]	CdfFromME.cdfFromME(Matrix alpha, Matrix A, double[] x)	Returns the cumulative distribution function of a matrix-exponential distribution.
static double[]	CdfFromME.cdfFromPH(double[] alpha, Matrix A, double[] x)	Overload for double[] alpha.
static double[]	CdfFromME.cdfFromPH(Matrix alpha, Matrix A, double[] x)	Returns the cumulative distribution function of a phase-type distribution.
static boolean	CheckMEPositiveDensity.checkMEPositiveDensity(Matrix alpha, Matrix A)
static boolean	CheckMEPositiveDensity.checkMEPositiveDensity(Matrix alpha, Matrix A, int maxSize)
static boolean	CheckMEPositiveDensity.checkMEPositiveDensity(Matrix alpha, Matrix A, int maxSize, double prec)	Checks if the given ME distribution has positive density.
static boolean	CheckMERepresentation.checkMERepresentation(double[] alpha, Matrix A)
static boolean	CheckMERepresentation.checkMERepresentation(double[] alpha, Matrix A, double prec)	Overload for double[] alpha.
static boolean	CheckMERepresentation.checkMERepresentation(Matrix alpha, Matrix A)
static boolean	CheckMERepresentation.checkMERepresentation(Matrix alpha, Matrix A, double prec)	Checks if the given vector and matrix define a valid matrix- exponential representation.
static boolean	CheckPHRepresentation.checkPHRepresentation(double[] alpha, Matrix A)
static boolean	CheckPHRepresentation.checkPHRepresentation(double[] alpha, Matrix A, double prec)	Overload for double[] alpha.
static boolean	CheckPHRepresentation.checkPHRepresentation(Matrix alpha, Matrix A)
static boolean	CheckPHRepresentation.checkPHRepresentation(Matrix alpha, Matrix A, double prec)	Checks if the given vector and matrix define a valid phase- type representation.
static boolean	CheckRAPRepresentation.checkRAPRepresentation(Matrix H0, Matrix H1)
static boolean	CheckRAPRepresentation.checkRAPRepresentation(Matrix H0, Matrix H1, double prec)	Checks if the given matrices define a valid Rational Arrival Process (RAP) representation.
PHRepresentation	PHRepresentation.copy(Matrix alpha, Matrix A)
static Pair<double[],double[]>	IntervalPdfFromPH.intervalPdfFromME(Matrix alpha, Matrix A, double[] intBounds)	Returns the approximate probability density function of a matrix-exponential distribution, based on the probability of falling into intervals.
static Pair<double[],double[]>	IntervalPdfFromPH.intervalPdfFromPH(Matrix alpha, Matrix A, double[] intBounds)	Returns the approximate probability density function of a continuous phase-type distribution, based on the probability of falling into intervals.
static int	MEOrder.meOrder(Matrix alpha, Matrix A)
static int	MEOrder.meOrder(Matrix alpha, Matrix A, String kind)
static int	MEOrder.meOrder(Matrix alpha, Matrix A, String kind, double prec)	Returns the order of the ME distribution (which is not necessarily equal to the size of the representation).
static MERepresentation	MinimalRepFromME.minimalRepFromME(Matrix alpha, Matrix A)
static MERepresentation	MinimalRepFromME.minimalRepFromME(Matrix alpha, Matrix A, String how)
static MERepresentation	MinimalRepFromME.minimalRepFromME(Matrix alpha, Matrix A, String how, double prec)	Returns the minimal representation of the given ME distribution.
static double[]	MomentsFromME.momentsFromME(double[] alpha, Matrix A)
static double[]	MomentsFromME.momentsFromME(double[] alpha, Matrix A, int K)	Overload for double[] alpha.
static double[]	MomentsFromME.momentsFromME(Matrix alpha, Matrix A)
static double[]	MomentsFromME.momentsFromME(Matrix alpha, Matrix A, int K)	Returns the first K moments of a matrix-exponential distribution.
static double[]	MomentsFromME.momentsFromPH(double[] alpha, Matrix A)
static double[]	MomentsFromME.momentsFromPH(double[] alpha, Matrix A, int K)	Overload for double[] alpha.
static double[]	MomentsFromME.momentsFromPH(Matrix alpha, Matrix A)
static double[]	MomentsFromME.momentsFromPH(Matrix alpha, Matrix A, int K)	Returns the first K moments of a phase-type distribution.
static PHRepresentation	MonocyclicPHFromME.monocyclicPHFromME(Matrix alpha, Matrix A)
static PHRepresentation	MonocyclicPHFromME.monocyclicPHFromME(Matrix alpha, Matrix A, int maxSize)
static PHRepresentation	MonocyclicPHFromME.monocyclicPHFromME(Matrix alpha, Matrix A, int maxSize, double prec)	Transforms an arbitrary matrix-exponential representation to a Markovian monocyclic representation.
static double[]	PdfFromME.pdfFromME(double[] alpha, Matrix A, double[] x)	Overload for double[] alpha.
static double[]	PdfFromME.pdfFromME(Matrix alpha, Matrix A, double[] x)	Returns the probability density function of a matrix-exponential distribution.
static double[]	PdfFromME.pdfFromPH(double[] alpha, Matrix A, double[] x)	Overload for double[] alpha.
static double[]	PdfFromME.pdfFromPH(Matrix alpha, Matrix A, double[] x)	Returns the probability density function of a phase-type distribution.
static PHRepresentation	PHFromME.phFromME(Matrix alpha, Matrix A)
static PHRepresentation	PHFromME.phFromME(Matrix alpha, Matrix A, double prec)	Obtains a Markovian representation of a matrix exponential distribution of the same size, if possible, using elementary similarity transformations.
static double[]	SamplesFromPH.samplesFromPH(double[] alpha, Matrix A, int K)
static double[]	SamplesFromPH.samplesFromPH(double[] alpha, Matrix A, int K, Random random)
static double[]	SamplesFromPH.samplesFromPH(Matrix alpha, Matrix A, int K)
static double[]	SamplesFromPH.samplesFromPH(Matrix alpha, Matrix A, int K, Random random)	Generates random samples from a phase-type distribution.

Constructors in jline.lib.butools.ph with parameters of type Matrix

Modifier	Constructor	Description
	MERepresentation(Matrix alpha, Matrix A)
	PH2Representation(Matrix alpha, Matrix A)
	PH3Representation(Matrix alpha, Matrix A)
	PHRepresentation(Matrix alpha, Matrix A)

Uses of Matrix in jline.lib.butools.queues

Methods in jline.lib.butools.queues with parameters of type Matrix

Modifier and Type	Method	Description
static FluFluResult	FluFluQueue.fluFluQueue(Matrix Qin, Matrix Rin, Matrix Qout, Matrix Rout, boolean srv0stop)
static FluFluResult	FluFluQueue.fluFluQueue(Matrix Qin, Matrix Rin, Matrix Qout, Matrix Rout, boolean srv0stop, int numFluidMoments, int numSojournMoments)
static FluFluResult	FluFluQueue.fluFluQueue(Matrix Qin, Matrix Rin, Matrix Qout, Matrix Rout, boolean srv0stop, int numFluidMoments, int numSojournMoments, double prec)	Returns various performance measures of a fluid queue with independent fluid arrival and service processes.
static Map<String,Object>	FluidQueue.fluidQueue(Matrix Q, Matrix Rin, Matrix Rout, Map<String,Object> measures)
static Map<String,Object>	FluidQueue.fluidQueue(Matrix Q, Matrix Rin, Matrix Rout, Map<String,Object> measures, Matrix Q0)
static Map<String,Object>	FluidQueue.fluidQueue(Matrix Q, Matrix Rin, Matrix Rout, Map<String,Object> measures, Matrix Q0, double prec)	Returns various performance measures of a fluid queue.
static Map<String,Object>	MAPMAP1.mapmap1(Matrix D0, Matrix D1, Matrix S0, Matrix S1, Map<String,Object> measures)
static Map<String,Object>	MAPMAP1.mapmap1(Matrix D0, Matrix D1, Matrix S0, Matrix S1, Map<String,Object> measures, double prec)	Returns various performance measures of a continuous time MAP/MAP/1 queue.
static Map<String,Object>	QBDQueue.qbdQueue(Matrix B, Matrix L, Matrix F, Matrix L0, Map<String,Object> measures)
static Map<String,Object>	QBDQueue.qbdQueue(Matrix B, Matrix L, Matrix F, Matrix L0, Map<String,Object> measures, double prec)	Returns various performance measures of a continuous time QBD queue.

Uses of Matrix in jline.lib.butools.reptrans

Methods in jline.lib.butools.reptrans that return Matrix

Modifier and Type	Method	Description
Matrix	MarkovianRepresentation.getB()
Matrix	MarkovianRepresentation.getBeta()
static Matrix	SimilarityMatrix.similarityMatrix(Matrix A1, Matrix A2)	Returns the matrix that transforms A1 to A2.
static Matrix	TransformToAcyclic.transformToAcyclic(Matrix A)
static Matrix	TransformToAcyclic.transformToAcyclic(Matrix A, int maxSize)
static Matrix	TransformToAcyclic.transformToAcyclic(Matrix A, int maxSize, double precision)	Transforms an arbitrary matrix to a Markovian bi-diagonal matrix.
static Matrix	TransformToMonocyclic.transformToMonocyclic(Matrix A)
static Matrix	TransformToMonocyclic.transformToMonocyclic(Matrix A, int maxSize)
static Matrix	TransformToMonocyclic.transformToMonocyclic(Matrix A, int maxSize, double precision)	Transforms an arbitrary matrix to a Markovian monocyclic matrix.

Methods in jline.lib.butools.reptrans that return types with arguments of type Matrix

Modifier and Type	Method	Description
List<Matrix>	FindMarkovianRepresentation.TransFun.apply(List<Matrix> rep, Matrix B)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, FindMarkovianRepresentation.TransFun transfun, FindMarkovianRepresentation.EvalFun evalfun, double precision)	Overload accepting Java functional-interface flavors of the arguments.
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun, double precision)	Obtains a Markovian representation from a non-Markovian one while keeping the size the same, by applying a series of elementary transformations.
static Pair<Matrix,Integer>	MStaircase.mStaircase(List<Matrix> Y, Matrix Z)
static Pair<Matrix,Integer>	MStaircase.mStaircase(List<Matrix> Y, Matrix Z, double precision)	Computes a smaller representation using the staircase algorithm.

Methods in jline.lib.butools.reptrans with parameters of type Matrix

Modifier and Type	Method	Description
List<Matrix>	FindMarkovianRepresentation.TransFun.apply(List<Matrix> rep, Matrix B)
static MarkovianRepresentation	ExtendToMarkovian.extendToMarkovian(Matrix alpha, Matrix A)
static MarkovianRepresentation	ExtendToMarkovian.extendToMarkovian(Matrix alpha, Matrix A, int maxSize)
static MarkovianRepresentation	ExtendToMarkovian.extendToMarkovian(Matrix alpha, Matrix A, int maxSize, double precision)	Extends a non-Markovian initial vector to a Markovian one by appending an Erlang tail.
static Pair<Matrix,Integer>	MStaircase.mStaircase(List<Matrix> Y, Matrix Z)
static Pair<Matrix,Integer>	MStaircase.mStaircase(List<Matrix> Y, Matrix Z, double precision)	Computes a smaller representation using the staircase algorithm.
static Matrix	SimilarityMatrix.similarityMatrix(Matrix A1, Matrix A2)	Returns the matrix that transforms A1 to A2.
static Matrix	TransformToAcyclic.transformToAcyclic(Matrix A)
static Matrix	TransformToAcyclic.transformToAcyclic(Matrix A, int maxSize)
static Matrix	TransformToAcyclic.transformToAcyclic(Matrix A, int maxSize, double precision)	Transforms an arbitrary matrix to a Markovian bi-diagonal matrix.
static Matrix	TransformToMonocyclic.transformToMonocyclic(Matrix A)
static Matrix	TransformToMonocyclic.transformToMonocyclic(Matrix A, int maxSize)
static Matrix	TransformToMonocyclic.transformToMonocyclic(Matrix A, int maxSize, double precision)	Transforms an arbitrary matrix to a Markovian monocyclic matrix.

Method parameters in jline.lib.butools.reptrans with type arguments of type Matrix

Modifier and Type	Method	Description
double	FindMarkovianRepresentation.EvalFun.apply(List<Matrix> rep, int k)
List<Matrix>	FindMarkovianRepresentation.TransFun.apply(List<Matrix> rep, Matrix B)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, FindMarkovianRepresentation.TransFun transfun, FindMarkovianRepresentation.EvalFun evalfun, double precision)	Overload accepting Java functional-interface flavors of the arguments.
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun)
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun, double precision)	Obtains a Markovian representation from a non-Markovian one while keeping the size the same, by applying a series of elementary transformations.
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun, double precision)	Obtains a Markovian representation from a non-Markovian one while keeping the size the same, by applying a series of elementary transformations.
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun, double precision)	Obtains a Markovian representation from a non-Markovian one while keeping the size the same, by applying a series of elementary transformations.
static List<Matrix>	FindMarkovianRepresentation.findMarkovianRepresentation(List<Matrix> rep, kotlin.jvm.functions.Function2<List<Matrix>,Matrix,List<Matrix>> transfun, kotlin.jvm.functions.Function2<List<Matrix>,Integer,Double> evalfun, double precision)	Obtains a Markovian representation from a non-Markovian one while keeping the size the same, by applying a series of elementary transformations.
static Pair<Matrix,Integer>	MStaircase.mStaircase(List<Matrix> Y, Matrix Z)
static Pair<Matrix,Integer>	MStaircase.mStaircase(List<Matrix> Y, Matrix Z, double precision)	Computes a smaller representation using the staircase algorithm.

Constructors in jline.lib.butools.reptrans with parameters of type Matrix

Modifier	Constructor	Description
	MarkovianRepresentation(Matrix beta, Matrix B)

Uses of Matrix in jline.lib.butools.trace

Methods in jline.lib.butools.trace that return Matrix

Modifier and Type	Method	Description
static Matrix	LagCorrelationsFromTrace.lagkJointMomentsFromTrace(double[] trace, int K)
static Matrix	LagCorrelationsFromTrace.lagkJointMomentsFromTrace(double[] trace, int K, int L)	Returns the lag-L joint moments of a trace.

Uses of Matrix in jline.lib.fjcodes

Fields in jline.lib.fjcodes declared as Matrix

Modifier and Type	Field	Description
final Matrix	ComputeT.ComputeTResult.A_jump
final Matrix	ReturnWaitResult.alfa
final Matrix	SRKResult.Kc
final Matrix	SRKResult.Ke
final Matrix	FJArrival.lambda0
final Matrix	FJArrival.lambda1
final Matrix	PiResult.pi0
final Matrix	SRKResult.R0
final Matrix	ComputeT.ComputeTResult.S
final Matrix	ComputeT.ComputeTResult.S_Arr
final Matrix	SRKResult.S_last
final Matrix	SRKResult.S_long
final Matrix	SRKResult.Se
final Matrix	SRKResult.Sestar
final Matrix	FJService.ST
final Matrix	ComputeT.ComputeTResult.sum_Ajump
final Matrix	ComputeT.ComputeTResult.T
final Matrix	FJService.tau_st
final Matrix	ReturnWaitResult.wait_alpha
final Matrix	ReturnWaitResult.wait_Smat

Methods in jline.lib.fjcodes that return Matrix

Modifier and Type	Method	Description
static Matrix	FjCodesUtilsKt.build_index(int m, int cr)	Build combinatorial index patterns: enumerate all ways to distribute cr items into m bins.
static Matrix	FJUtils.build_index(int m, int cr)	Build combinatorial index patterns.
Matrix	ComputeT.ComputeTResult.component1()
Matrix	GenerateServiceResult.component1()
Matrix	SAResult.component1()
Matrix	ComputeT.ComputeTResult.component2()
Matrix	SAResult.component2()
Matrix	ComputeT.ComputeTResult.component3()
Matrix	ComputeT.ComputeTResult.component4()
Matrix	ComputeT.ComputeTResult.component5()
static Matrix	ComputeT_NARE.computeT_NARE(Matrix D0, Matrix D1, Matrix S, Matrix A_jump)
static Matrix	ComputeT_Sylvester.computeT_Sylvester(Matrix D0, Matrix D1, Matrix S, Matrix A_jump)	Compute T-matrix via Sylvester equation method
static Matrix	FJStateSpace.constructNotAllBusy(int C, FJService services, FJServiceH service_h)	Construct state space matrix for not-all-busy states.
Matrix	SAResult.getA_jump()
Matrix	ReturnWaitResult.getAlfa()
Matrix	FJServiceH.getBeta()
Matrix	SRKResult.getKc()
Matrix	SRKResult.getKe()
Matrix	FJArrival.getLambda0()
Matrix	FJArrival.getLambda1()
Matrix	PiResult.getPi0()
Matrix	SRKResult.getR0()
Matrix	FJServiceH.getS()
Matrix	SAResult.getS()
Matrix	SRKResult.getS_last()
Matrix	SRKResult.getS_long()
Matrix	SRKResult.getSe()
Matrix	FJServiceH.getService_phases()
Matrix	SRKResult.getSestar()
Matrix	FJService.getSt()
Matrix	FJService.getST()
Matrix	GenerateServiceResult.getT()
Matrix	FJService.getTau_st()
Matrix	ReturnWaitResult.getWait_alpha()
Matrix	ReturnWaitResult.getWait_Smat()
static Matrix	FjCodesUtilsKt.kronsum(Matrix A, Matrix B)	Compute Kronecker sum of two matrices: A xor B = A x I + I x B.
static Matrix	FJUtils.kronsum(Matrix A, Matrix B)	Compute Kronecker sum of two matrices.
static Matrix	ReturnPer.returnPer(Matrix vector, Matrix matrix, double[] pers)	Extract percentiles from a Phase-Type (PH) distribution
static Matrix	ReturnRT1.returnRT1(FJArrival arrival, FJService service, double[] pers)	Compute response time percentiles for K=1 Fork-Join queue.
static Matrix	ReturnRT2.returnRT2(FJArrival arrival, FJService service, double[] pers, int C)
static Matrix	ReturnRT2.returnRT2(FJArrival arrival, FJService service, double[] pers, int C, String tMode)	Compute response time percentiles for K=2 Fork-Join queue.

Methods in jline.lib.fjcodes with parameters of type Matrix

Modifier and Type	Method	Description
static PiResult	ComputePi.computePi(Matrix T, FJArrival arrival, FJService services, FJServiceH service_h, int C, Matrix S, Matrix A_jump)	Compute steady-state distribution for the case with 2 replicas.
static Matrix	ComputeT_NARE.computeT_NARE(Matrix D0, Matrix D1, Matrix S, Matrix A_jump)
static Matrix	ComputeT_Sylvester.computeT_Sylvester(Matrix D0, Matrix D1, Matrix S, Matrix A_jump)	Compute T-matrix via Sylvester equation method
static SRKResult	FJStateSpace.constructSRK(int C, FJService services, FJServiceH service_h, Matrix S)	Construct extended state space matrices (Se, Sestar, R0, Ke, Kc).
static GenerateServiceResult	GenerateService.generateService(FJService services, FJServiceH service_h, int C, Matrix S)	Generate Phase-Type representation for service time.
static double[]	FjCodesUtilsKt.getRowAsArray(Matrix matrix, int row)	Extract row row of matrix as a double[].
static double[]	FJUtils.getRowAsArray(Matrix matrix, int row)	Extract a row from a Matrix as a double[].
static Matrix	FjCodesUtilsKt.kronsum(Matrix A, Matrix B)	Compute Kronecker sum of two matrices: A xor B = A x I + I x B.
static Matrix	FJUtils.kronsum(Matrix A, Matrix B)	Compute Kronecker sum of two matrices.
static Matrix	ReturnPer.returnPer(Matrix vector, Matrix matrix, double[] pers)	Extract percentiles from a Phase-Type (PH) distribution
static ReturnWaitResult	ReturnWait.returnWait(double En1, Matrix pi0, Matrix T, Matrix phi, Matrix sum_Ajump)	Compute Phase-Type representation of stationary waiting time.
static void	FjCodesUtilsKt.setSubMatrix(Matrix target, int startRow, int startCol, Matrix source)	Copy source into target starting at the given (0-based) row/column position.
static void	FJUtils.setSubMatrix(Matrix target, int startRow, int startCol, Matrix source)	Copy a submatrix into a target matrix at specified position.
static int	FjCodesUtilsKt.vectmatch(double[] row, Matrix matrix)	Find the 1-based index of the row in matrix that matches row elementwise (within 1e-10), or -1 if no row matches.
static int	FJUtils.vectmatch(double[] row, Matrix matrix)	Find the row index in a matrix that matches a given row vector.

Constructors in jline.lib.fjcodes with parameters of type Matrix

Modifier	Constructor	Description
	ComputeTResult(Matrix T, Matrix S, Matrix A_jump, Matrix S_Arr, Matrix sum_Ajump)
	FJArrival(double lambda, Matrix lambda0, Matrix lambda1, int ArrChoice)
	FJService(double mu, Matrix ST, Matrix St, Matrix tau_st, int SerChoice)
	FJServiceH(Matrix service_phases, Matrix beta, Matrix S)
	GenerateServiceResult(Matrix T, int newdim, int dim_notbusy)
	PiResult(Matrix pi0, double En1)
	ReturnWaitResult(Matrix wait_alpha, Matrix wait_Smat, double prob_wait, Matrix alfa)
	SAResult(Matrix S, Matrix A_jump)
	SRKResult(Matrix Se, Matrix Sestar, Matrix R0, Matrix Ke, Matrix Kc, Matrix S_long, Matrix S_last)

Uses of Matrix in jline.lib.kpctoolbox

Methods in jline.lib.kpctoolbox that return Matrix

Modifier and Type	Method	Description
static Matrix	Kpctoolbox.autocov(Matrix S)
static Matrix	MarkovChain.ctmcSteadyState(Matrix Q)
static Matrix	MarkovChain.ctmcTransient(Matrix Q, double t)
static Matrix	MarkovChain.dtmcSteadyState(Matrix P)
static Matrix	Kpctoolbox.eye(int n)
static Matrix	Kpctoolbox.ones(int m, int n)
static Matrix	Kpctoolbox.trace_acf(Matrix S, int maxLag)
static Matrix	Kpctoolbox.trace_bicov(Matrix S, int[] grid)
static Matrix	Kpctoolbox.trace_bicov(Matrix S1, Matrix S2, int maxLag)
static Matrix	Kpctoolbox.trace_gamma(Matrix S, int limit)
static Matrix	Kpctoolbox.trace_iat2bins(Matrix S, int numBins)
static Matrix	Kpctoolbox.trace_iat2counts(Matrix S, int numBins)
static Matrix	Kpctoolbox.trace_pmf(Matrix S)
static Matrix	Kpctoolbox.trace_shuffle(Matrix S)
static Matrix	Kpctoolbox.zeros(int m, int n)

Methods in jline.lib.kpctoolbox that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	APH.fromMoments(Matrix moments)
static Pair<Matrix,Matrix>	APH.fromMoments(Matrix moments)

Methods in jline.lib.kpctoolbox with parameters of type Matrix

Modifier and Type	Method	Description
static Matrix	Kpctoolbox.autocov(Matrix S)
static Matrix	MarkovChain.ctmcSteadyState(Matrix Q)
static Matrix	MarkovChain.ctmcTransient(Matrix Q, double t)
static Matrix	MarkovChain.dtmcSteadyState(Matrix P)
static MatrixCell	MMPP2.fit(Matrix moments)
static MatrixCell	MMPP2.fit(Matrix moments, double acf1)
static MatrixCell	MMPP2.fit1(Matrix moments)
static MatrixCell	MMPP2.fit2(Matrix moments, double acf1)
static MatrixCell	MMPP2.fit3(Matrix moments, double acf1, double acf2)
static Pair<Matrix,Matrix>	APH.fromMoments(Matrix moments)
static int	Kpctoolbox.maxpos(Matrix data)
static int	Kpctoolbox.minpos(Matrix data)
static double	Kpctoolbox.mvph_corr(Matrix alpha, Matrix A, Matrix B, Matrix C)
static double	Kpctoolbox.mvph_cov(Matrix alpha, Matrix A, Matrix B, Matrix C)
static double	Kpctoolbox.mvph_joint(Matrix alpha, Matrix A, Matrix B, Matrix C, Matrix x, Matrix y)
static double	Kpctoolbox.mvph_mean_x(Matrix alpha, Matrix A, Matrix B)
static double	Kpctoolbox.mvph_mean_y(Matrix alpha, Matrix A, Matrix C)
static Matrix	Kpctoolbox.trace_acf(Matrix S, int maxLag)
static Matrix	Kpctoolbox.trace_bicov(Matrix S, int[] grid)
static Matrix	Kpctoolbox.trace_bicov(Matrix S1, Matrix S2, int maxLag)
static Matrix	Kpctoolbox.trace_gamma(Matrix S, int limit)
static Matrix	Kpctoolbox.trace_iat2bins(Matrix S, int numBins)
static Matrix	Kpctoolbox.trace_iat2counts(Matrix S, int numBins)
static double	Kpctoolbox.trace_idc(Matrix S, double timeWindow)
static double	Kpctoolbox.trace_idi(Matrix S, int numIntervals)
static double	Kpctoolbox.trace_joint(Matrix S, Matrix lags, Matrix orders)
static double	Kpctoolbox.trace_mean(Matrix S)
static Matrix	Kpctoolbox.trace_pmf(Matrix S)
static double	Kpctoolbox.trace_scv(Matrix S)
static Matrix	Kpctoolbox.trace_shuffle(Matrix S)
static double	Kpctoolbox.trace_skew(Matrix S)
static TraceAnalysis.TraceSummary	Kpctoolbox.trace_summary(Matrix S)
static double	Kpctoolbox.trace_var(Matrix S)

Method parameters in jline.lib.kpctoolbox with type arguments of type Matrix

Modifier and Type	Method	Description
static double	Kpctoolbox.mtrace_mean(List<Matrix> traces)
static double	Kpctoolbox.mtrace_var(List<Matrix> traces)

Uses of Matrix in jline.lib.kpctoolbox.aph

Methods in jline.lib.kpctoolbox.aph that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<double[],Matrix>	APH.aph_convpara(List<Pair<double[],Matrix>> distributions)
static Pair<double[],Matrix>	APH.aph_convseq(List<Pair<double[],Matrix>> distributions)
static Pair<double[],Matrix>	APH.aph_simplify(double[] a1, Matrix T1, double[] a2, Matrix T2, double p1, double p2, APH.ConvolutionPattern pattern)
static Pair<double[],Matrix>	APH.aph_simplify(double[] a1, Matrix T1, double[] a2, Matrix T2, APH.ConvolutionPattern pattern)

Methods in jline.lib.kpctoolbox.aph with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<double[],Matrix>	APH.aph_simplify(double[] a1, Matrix T1, double[] a2, Matrix T2, double p1, double p2, APH.ConvolutionPattern pattern)
static Pair<double[],Matrix>	APH.aph_simplify(double[] a1, Matrix T1, double[] a2, Matrix T2, APH.ConvolutionPattern pattern)

Method parameters in jline.lib.kpctoolbox.aph with type arguments of type Matrix

Modifier and Type	Method	Description
static Pair<double[],Matrix>	APH.aph_convpara(List<Pair<double[],Matrix>> distributions)
static Pair<double[],Matrix>	APH.aph_convseq(List<Pair<double[],Matrix>> distributions)

Uses of Matrix in jline.lib.kpctoolbox.basic

Methods in jline.lib.kpctoolbox.basic that return Matrix

Modifier and Type	Method	Description
Matrix	SpectralDecomposition.component3()
Matrix	SpectralDecomposition.component4()
static Matrix	BasicUtils.e(int n)	Creates a vector e(n) = [1, 1, ..., 1]^T used in matrix operations.
static Matrix	BasicUtils.eye(int n)	Creates an identity matrix.
Matrix	SpectralDecomposition.getEigenvalueMatrix()
Matrix	SpectralDecomposition.getEigenvectors()
static Matrix	BasicUtils.ones(int n)	Creates a column vector of ones.
static Matrix	BasicUtils.zeros(int m, int n)	Creates a zero matrix.

Methods in jline.lib.kpctoolbox.basic that return types with arguments of type Matrix

Modifier and Type	Method	Description
List<Matrix>	SpectralDecomposition.component2()
List<Matrix>	SpectralDecomposition.getProjectors()

Methods in jline.lib.kpctoolbox.basic with parameters of type Matrix

Modifier and Type	Method	Description
static SpectralDecomposition	BasicUtils.spectd(Matrix A)	Computes the spectral decomposition of a matrix.

Constructors in jline.lib.kpctoolbox.basic with parameters of type Matrix

Modifier	Constructor	Description
	SpectralDecomposition(double[] spectrum, List<Matrix> projectors, Matrix eigenvectors, Matrix eigenvalueMatrix)

Constructor parameters in jline.lib.kpctoolbox.basic with type arguments of type Matrix

Modifier	Constructor	Description
	SpectralDecomposition(double[] spectrum, List<Matrix> projectors, Matrix eigenvectors, Matrix eigenvalueMatrix)

Uses of Matrix in jline.lib.kpctoolbox.mc

Fields in jline.lib.kpctoolbox.mc declared as Matrix

Modifier and Type	Field	Description
final Matrix	CTMC.CTMCSolveResult.generator

Methods in jline.lib.kpctoolbox.mc that return Matrix

Modifier and Type	Method	Description
static Matrix	CTMC.ctmc_makeinfgen(Matrix Q)	Normalizes a matrix to be a valid infinitesimal generator.
static Matrix	CTMC.ctmc_rand(int n)	Generates a random infinitesimal generator matrix.
static Matrix	CTMC.ctmc_timereverse(Matrix Q)	Computes the time-reversed generator of a CTMC.
static Matrix	DTMC.dtmc_makestochastic(Matrix P)
static Matrix	DTMC.dtmc_rand(int n)
static Matrix	DTMC.dtmc_stochcomp(Matrix P)
static Matrix	DTMC.dtmc_stochcomp(Matrix P, int[] I)
static Matrix	DTMC.dtmc_timereverse(Matrix P)

Methods in jline.lib.kpctoolbox.mc that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Double>	CTMC.ctmc_randomization(Matrix Q)
static Pair<Matrix,Double>	CTMC.ctmc_randomization(Matrix Q, Double q)	Applies uniformization (randomization) to transform a CTMC into a DTMC.

Methods in jline.lib.kpctoolbox.mc with parameters of type Matrix

Modifier and Type	Method	Description
static Matrix	CTMC.ctmc_makeinfgen(Matrix Q)	Normalizes a matrix to be a valid infinitesimal generator.
static Pair<Matrix,Double>	CTMC.ctmc_randomization(Matrix Q)
static Pair<Matrix,Double>	CTMC.ctmc_randomization(Matrix Q, Double q)	Applies uniformization (randomization) to transform a CTMC into a DTMC.
static double[]	CTMC.ctmc_relsolve(Matrix Q)	Computes the equilibrium distribution relative to a reference state.
static double[]	CTMC.ctmc_relsolve(Matrix Q, int refstate)
static double[]	CTMC.ctmc_solve(Matrix Q)	Computes the equilibrium distribution of a continuous-time Markov chain.
static CTMC.CTMCSolveResult	CTMC.ctmc_solveFull(Matrix Q)	Computes the equilibrium distribution with full details.
static Matrix	CTMC.ctmc_timereverse(Matrix Q)	Computes the time-reversed generator of a CTMC.
static Pair<double[],Integer>	CTMC.ctmc_uniformization(double[] pi0, Matrix Q, double t)	Computes transient probabilities using uniformization method.
static Pair<double[],Integer>	CTMC.ctmc_uniformization(double[] pi0, Matrix Q, double t, double tol, int maxiter)
static int	DTMC.dtmc_isfeasible(Matrix P)
static Matrix	DTMC.dtmc_makestochastic(Matrix P)
static int[]	DTMC.dtmc_simulate(Matrix P, double[] pi0, int nSteps)
static double[]	DTMC.dtmc_solve(Matrix P)
static Matrix	DTMC.dtmc_stochcomp(Matrix P)
static Matrix	DTMC.dtmc_stochcomp(Matrix P, int[] I)
static Matrix	DTMC.dtmc_timereverse(Matrix P)
static Pair<double[],Integer>	DTMC.dtmc_uniformization(double[] pi0, Matrix P)
static Pair<double[],Integer>	DTMC.dtmc_uniformization(double[] pi0, Matrix P, double t)
static Pair<double[],Integer>	DTMC.dtmc_uniformization(double[] pi0, Matrix P, double t, double tol)
static Pair<double[],Integer>	DTMC.dtmc_uniformization(double[] pi0, Matrix P, double t, double tol, int maxiter)
static CTMC.ConnectedComponents	CTMC.weaklyconncomp(Matrix G)	Finds weakly connected components in a directed graph.

Constructors in jline.lib.kpctoolbox.mc with parameters of type Matrix

Modifier	Constructor	Description
	CTMCSolveResult(double[] equilibriumDistribution, Matrix generator, int numComponents, int[] componentAssignment)

Uses of Matrix in jline.lib.kpctoolbox.mvph

Methods in jline.lib.kpctoolbox.mvph with parameters of type Matrix

Modifier and Type	Method	Description
static double	MVPH.mvph_corr(double[] alpha, Matrix S, Matrix T, Matrix D)
static double	MVPH.mvph_cov(double[] alpha, Matrix S, Matrix T, Matrix D)
static double	MVPH.mvph_joint(double[] alpha, Matrix S, Matrix T, Matrix D, int n1, int n2)	Computes the joint moment E[X^n1 * Y^n2] of a bivariate phase-type distribution.
static double	MVPH.mvph_mean_x(double[] alpha, Matrix S, Matrix T, Matrix D)
static double	MVPH.mvph_mean_y(double[] alpha, Matrix S, Matrix T, Matrix D)

Uses of Matrix in jline.lib.kpctoolbox.smp

Methods in jline.lib.kpctoolbox.smp that return Matrix

Modifier and Type	Method	Description
static Matrix	DET.det_embedded(MatrixCell DET)

Uses of Matrix in jline.lib.m3a

Methods in jline.lib.m3a with parameters of type Matrix

Modifier and Type	Method	Description
static MTrace	M3aFit.m3afit_init(Matrix S, Matrix C)	Prepares multiclass trace for M3A fitting from Matrix inputs.

Uses of Matrix in jline.lib.perm

Fields in jline.lib.perm declared as Matrix

Modifier and Type	Field	Description
final Matrix	PermSolver.matrix

Methods in jline.lib.perm that return Matrix

Modifier and Type	Method	Description
Matrix	PermSolver.getMatrix()

Methods in jline.lib.perm that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Double>	QueueingNetwork.preprocessingDS(Matrix M)	Make a matrix doubly stochastic via the Sinkhorn algorithm.

Methods in jline.lib.perm with parameters of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Double>	QueueingNetwork.preprocessingDS(Matrix M)	Make a matrix doubly stochastic via the Sinkhorn algorithm.

Constructors in jline.lib.perm with parameters of type Matrix

Modifier	Constructor	Description
	AdaPartSampler(Matrix matrix)
	AdaPartSampler(Matrix matrix, int maximumAcceptedSamples, long maximumTime, int maximumSamples, String mode, boolean solve)
	BethePermanent(Matrix matrix)
	BethePermanent(Matrix matrix, double epsilon, int maxIteration)
	BethePermanent(Matrix matrix, double epsilon, int maxIteration, boolean solve)
	HeuristicPermanent(Matrix matrix)	Constructor with just matrix parameter.
	HeuristicPermanent(Matrix matrix, boolean solve)	Constructor with just matrix and solve parameters.
	HeuristicPermanent(Matrix matrix, double tolerance, int maxIterations, boolean solve)	Constructor with all parameters.
	HuberLawSampler(Matrix matrix)
	HuberLawSampler(Matrix matrix, double delta, double alpha2, double epsilon, String mode, int numberOfSamples, long maximumTime, boolean solve)
	NaivePermanent(Matrix matrix)
	NaivePermanent(Matrix matrix, boolean solve)
	Permanent(Matrix matrix)
	Permanent(Matrix matrix, boolean solve)
	PermSolver(Matrix matrix)
	RyzerPermanent(Matrix matrix)
	RyzerPermanent(Matrix matrix, String mode)
	RyzerPermanent(Matrix matrix, String mode, boolean solve)

Uses of Matrix in jline.lib.qmam

Fields in jline.lib.qmam declared as Matrix

Modifier and Type	Field	Description
final Matrix	MMAPKPHK1Result.qlTotal
final Matrix	MAPDcResult.queueLength
final Matrix	MAPMAP1Result.queueLength
final Matrix	MAPMcResult.queueLength
final Matrix	PHPH1Result.queueLength
final Matrix	Q_RAP_RAP_1.RAPRAP1Result.queueLength
final Matrix	MAPMAP1Result.Smat
final Matrix	MAPMcResult.Smat
final Matrix	MMAPKPHK1Result.Smat
final Matrix	MAPMAP1Result.sojAlpha
final Matrix	MAPMAP1Result.waitAlpha
final Matrix	MAPMcResult.waitAlpha
final Matrix	PHPH1Result.waitAlpha
final Matrix	MAPDcResult.waitingTime
final Matrix	PHPH1Result.waitT

Fields in jline.lib.qmam with type parameters of type Matrix

Modifier and Type	Field	Description
final List<Matrix>	MMAPKPHK1Result.qlPerType
final List<Matrix>	MMAPKPHK1Result.sojAlpha
final List<Matrix>	MMAPKPHK1Result.waitAlpha

Methods in jline.lib.qmam that return Matrix

Modifier and Type	Method	Description
Matrix	MAPMAP1Result.component1()
Matrix	PHPH1Result.component1()
Matrix	MAPMAP1Result.component2()
Matrix	PHPH1Result.component2()
Matrix	MAPMAP1Result.component3()
Matrix	PHPH1Result.component3()
Matrix	MAPMAP1Result.component4()
Matrix	MMAPKPHK1Result.getQlTotal()
Matrix	MAPDcResult.getQueueLength()
Matrix	MAPMAP1Result.getQueueLength()
Matrix	MAPMcResult.getQueueLength()
Matrix	PHPH1Result.getQueueLength()
Matrix	MAPMAP1Result.getSmat()
Matrix	MAPMcResult.getSmat()
Matrix	MMAPKPHK1Result.getSmat()
Matrix	MAPMAP1Result.getSojAlpha()
Matrix	MAPMAP1Result.getWaitAlpha()
Matrix	MAPMcResult.getWaitAlpha()
Matrix	PHPH1Result.getWaitAlpha()
Matrix	MAPDcResult.getWaitingTime()
Matrix	PHPH1Result.getWaitT()
static Matrix	Q_Sylvest.qSylvest(Matrix U, Matrix T, Matrix B)	Solves the equation X*kron(A,I)+BX=-I using a Schur-based approach.

Methods in jline.lib.qmam that return types with arguments of type Matrix

Modifier and Type	Method	Description
List<Matrix>	MMAPKPHK1Result.getQlPerType()
List<Matrix>	MMAPKPHK1Result.getSojAlpha()
List<Matrix>	MMAPKPHK1Result.getWaitAlpha()
static Pair<Matrix,Matrix>	Q_Sylvest.schurDecomposition(Matrix A)	Performs Schur decomposition of a matrix.
static Pair<Matrix,Matrix>	Q_Sylvest.schurDecomposition(Matrix A)	Performs Schur decomposition of a matrix.

Methods in jline.lib.qmam with parameters of type Matrix

Modifier and Type	Method	Description
static MAPDcResult	Q_CT_MAP_D_C.qCtMapDC(Matrix D0, Matrix D1, double s, int c)
static MAPDcResult	Q_CT_MAP_D_C.qCtMapDC(Matrix D0, Matrix D1, double s, int c, MAPDcOptions options)	Computes queue length and waiting time distribution for a MAP/D/c/FCFS queue.
static MAPMAP1Result	Q_CT_MAP_MAP_1.qCtMapMap1(Matrix C0, Matrix C1, Matrix D0, Matrix D1)
static MAPMAP1Result	Q_CT_MAP_MAP_1.qCtMapMap1(Matrix C0, Matrix C1, Matrix D0, Matrix D1, MAPMAP1Options options)	Computes queue length and time distributions for a MAP/MAP/1/FCFS queue.
static MAPMcResult	Q_CT_MAP_M_C.qCtMapMC(Matrix D0, Matrix D1, double mu, int c)
static MAPMcResult	Q_CT_MAP_M_C.qCtMapMC(Matrix D0, Matrix D1, double mu, int c, MAPMcOptions options)
static MMAPKPHK1Result	Q_CT_MMAPK_PHK_1.qCtMmapkPhk1(Matrix D0, List<Matrix> D, List<Matrix> alpha, List<Matrix> S)
static MMAPKPHK1Result	Q_CT_MMAPK_PHK_1.qCtMmapkPhk1(Matrix D0, List<Matrix> D, List<Matrix> alpha, List<Matrix> S, MMAPKPHK1Options options)
static PHPH1Result	Q_CT_PH_PH_1.qCtPhPh1(Matrix alpha, Matrix T, Matrix beta, Matrix S)
static PHPH1Result	Q_CT_PH_PH_1.qCtPhPh1(Matrix alpha, Matrix T, Matrix beta, Matrix S, PHPH1Options options)	Computes queue length and waiting time distribution for a PH/PH/1/FCFS queue.
static Q_RAP_RAP_1.RAPRAP1Result	Q_RAP_RAP_1.qRapRap1(Matrix C0, Matrix C1, Matrix D0, Matrix D1)
static Q_RAP_RAP_1.RAPRAP1Result	Q_RAP_RAP_1.qRapRap1(Matrix C0, Matrix C1, Matrix D0, Matrix D1, Q_RAP_RAP_1.RAPRAP1Options options)	Computes queue length distribution for a RAP/RAP/1/FCFS queue.
static Matrix	Q_Sylvest.qSylvest(Matrix U, Matrix T, Matrix B)	Solves the equation X*kron(A,I)+BX=-I using a Schur-based approach.
static Pair<Matrix,Matrix>	Q_Sylvest.schurDecomposition(Matrix A)	Performs Schur decomposition of a matrix.

Method parameters in jline.lib.qmam with type arguments of type Matrix

Modifier and Type	Method	Description
static MMAPKPHK1Result	Q_CT_MMAPK_PHK_1.qCtMmapkPhk1(Matrix D0, List<Matrix> D, List<Matrix> alpha, List<Matrix> S)
static MMAPKPHK1Result	Q_CT_MMAPK_PHK_1.qCtMmapkPhk1(Matrix D0, List<Matrix> D, List<Matrix> alpha, List<Matrix> S, MMAPKPHK1Options options)

Constructors in jline.lib.qmam with parameters of type Matrix

Modifier	Constructor	Description
	MAPDcResult(Matrix queueLength, Matrix waitingTime)
	MAPMAP1Result(Matrix queueLength, Matrix sojAlpha, Matrix waitAlpha, Matrix Smat)
	MAPMcResult(Matrix queueLength, Matrix waitAlpha, Matrix Smat)
	MMAPKPHK1Result(List<Matrix> qlPerType, Matrix qlTotal, List<Matrix> sojAlpha, List<Matrix> waitAlpha, Matrix Smat)
	PHPH1Result(Matrix queueLength, Matrix waitAlpha, Matrix waitT)
	RAPRAP1Result(Matrix queueLength)

Constructor parameters in jline.lib.qmam with type arguments of type Matrix

Modifier	Constructor	Description
	MMAPKPHK1Result(List<Matrix> qlPerType, Matrix qlTotal, List<Matrix> sojAlpha, List<Matrix> waitAlpha, Matrix Smat)

Uses of Matrix in jline.lib.smc

Fields in jline.lib.smc declared as Matrix

Modifier and Type	Field	Description
final Matrix	GIM1PiOptions.boundary
final Matrix	MG1_ETAQA.ETAQAResult.G
final Matrix	MG1_ETAQA.ETAQAResult.pi

Methods in jline.lib.smc that return Matrix

Modifier and Type	Method	Description
Matrix	GIM1PiOptions.component1()
Matrix	GIM1CaudalResult.component2()
Matrix	MG1DecayResult.component2()
Matrix	GIM1PiOptions.getBoundary()
Matrix	MG1PiOptions.getBoundary()
Matrix	MG1_ETAQA.ETAQAResult.getG()
Matrix	MG1_ETAQA.ETAQAResult.getPi()
Matrix	MG1FIOptions.getStartValue()
Matrix	MG1DecayResult.getUT()
Matrix	GIM1CaudalResult.getV()
static Matrix	GIM1_pi.gim1_pi(Matrix B, Matrix R)
static Matrix	GIM1_pi.gim1_pi(Matrix B, Matrix R, GIM1PiOptions options)	Computes the stationary distribution of a GI/M/1-type Markov chain.
static Matrix	GIM1_R.gim1_R(Matrix A)
static Matrix	GIM1_R.gim1_R(Matrix A, GIM1_R.GIM1ROptions options)	Computes the R matrix for a GI/M/1-type Markov chain.
static Matrix	MG1_pi.mg1_cr(Matrix A)	Computes the G matrix using Cyclic Reduction for M/G/1-type Markov Chains.
static Matrix	MG1_pi.mg1_cr(Matrix A, MG1CROptions options)
static Matrix	MG1_EG.mg1_eg(Matrix A)
static Matrix	MG1_EG.mg1_eg(Matrix A, boolean verbose)	Determines G directly if rank(A0)=1 for M/G/1-type Markov chains.
static Matrix	MG1_FI.mg1_fi(Matrix A)
static Matrix	MG1_FI.mg1_fi(Matrix A, MG1FIOptions options)	Functional Iterations for M/G/1-Type Markov Chains.
static Matrix	MG1_ETAQA.mg1_g_etaqa(Matrix A)	Computes the G matrix for M/G/1-type Markov chains.
static Matrix	MG1_pi.mg1_pi(Matrix B, Matrix A)
static Matrix	MG1_pi.mg1_pi(Matrix B, Matrix A, MG1PiOptions options)
static Matrix	MG1_ETAQA.mg1_pi_etaqa(Matrix B, Matrix A)
static Matrix	MG1_ETAQA.mg1_pi_etaqa(Matrix B, Matrix A, Matrix G)
static Matrix	MG1_ETAQA.mg1_pi_etaqa(Matrix B, Matrix A, Matrix G, Matrix C0)	Computes the aggregated stationary probability vector for an M/G/1-type Markov chain using the ETAQA method.
static Matrix	NSF_GHT.nsfGht(Matrix A, int N)
static Matrix	NSF_GHT.nsfGht(Matrix A, int N, NSFGHTOptions options)	Gail-Hantler-Taylor algorithm for Non-Skip-Free Markov chains.
static Matrix	NSF_GHT.nsfPi(Matrix B, Matrix A, Matrix G)
static Matrix	NSF_GHT.nsfPi(Matrix B, Matrix A, Matrix G, NSFPiOptions options)	NSF_pi - Stationary vector of a Non-Skip-Free Markov chain.
static Matrix	QBD_NI_Sylvest.QBD_NI_Sylvest(Matrix A, Matrix B, Matrix C, Matrix D)	Solves the Sylvester equation AXB + CX = D using complex Schur and Hessenberg-triangular decomposition.
static Matrix	QBD_pi.QBD_pi(Matrix B0, Matrix B1, Matrix R)	QBD_pi: Stationary vector of a Quasi-Birth-Death Markov Chains [Neuts]
static Matrix	QBD_pi.QBD_pi(Matrix B0, Matrix B1, Matrix R, int MaxNumComp, int Verbose, Matrix Boundary, int RAPComp)
static Matrix	Stat.stat(Matrix A)

Methods in jline.lib.smc that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Quadruple<Matrix,Double,Double,Matrix>	MG1_Shifts.mg1_shifts(Matrix A)
static Quadruple<Matrix,Double,Double,Matrix>	MG1_Shifts.mg1_shifts(Matrix A)
static Quadruple<Matrix,Double,Double,Matrix>	MG1_Shifts.mg1_shifts(Matrix A, String shiftType)	Applies the shift technique to an M/G/1-type block matrix.
static Quadruple<Matrix,Double,Double,Matrix>	MG1_Shifts.mg1_shifts(Matrix A, String shiftType)	Applies the shift technique to an M/G/1-type block matrix.
static Map<String,Matrix>	QBD_CR.QBD_CR(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_EG.QBD_EG(Matrix A0, Matrix A1, Matrix A2, boolean optVerbose)
static Map<String,Matrix>	QBD_FI.QBD_FI(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Matrix StartValue_, Integer RAPComp_)
static Map<String,Matrix>	QBD_IS.QBD_IS(Matrix A0, Matrix A1, Matrix A2, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_LR.QBD_LR(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_NI.QBD_NI(Matrix A0, Matrix A1, Matrix A2, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_CR.solve(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)	Convenience alias for callers that expect a solve(...) entry point on the QBD_CR class.
static Map<String,Matrix>	QBD_FI.solve(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Matrix StartValue_, Integer RAPComp_)	Convenience alias for callers that expect a solve(...) entry point on the QBD_FI class.

Methods in jline.lib.smc with parameters of type Matrix

Modifier and Type	Method	Description
static GIM1CaudalResult	GIM1_Caudal.gim1_caudal(Matrix A)
static GIM1CaudalResult	GIM1_Caudal.gim1_caudal(Matrix A, boolean dual)
static GIM1CaudalResult	GIM1_Caudal.gim1_caudal(Matrix A, boolean dual, boolean computeEigenvector)	Computes the dominant eigenvalue of the R matrix for GI/M/1-type chains.
static Matrix	GIM1_pi.gim1_pi(Matrix B, Matrix R)
static Matrix	GIM1_pi.gim1_pi(Matrix B, Matrix R, GIM1PiOptions options)	Computes the stationary distribution of a GI/M/1-type Markov chain.
static Matrix	GIM1_R.gim1_R(Matrix A)
static Matrix	GIM1_R.gim1_R(Matrix A, GIM1_R.GIM1ROptions options)	Computes the R matrix for a GI/M/1-type Markov chain.
static Matrix	MG1_pi.mg1_cr(Matrix A)	Computes the G matrix using Cyclic Reduction for M/G/1-type Markov Chains.
static Matrix	MG1_pi.mg1_cr(Matrix A, MG1CROptions options)
static MG1DecayResult	MG1_Decay.mg1_decay(Matrix A)
static MG1DecayResult	MG1_Decay.mg1_decay(Matrix A, boolean computeEigenvector)	Computes the decay rate of a recurrent M/G/1 type Markov chain.
static Matrix	MG1_EG.mg1_eg(Matrix A)
static Matrix	MG1_EG.mg1_eg(Matrix A, boolean verbose)	Determines G directly if rank(A0)=1 for M/G/1-type Markov chains.
static Matrix	MG1_FI.mg1_fi(Matrix A)
static Matrix	MG1_FI.mg1_fi(Matrix A, MG1FIOptions options)	Functional Iterations for M/G/1-Type Markov Chains.
static Matrix	MG1_ETAQA.mg1_g_etaqa(Matrix A)	Computes the G matrix for M/G/1-type Markov chains.
static Matrix	MG1_pi.mg1_pi(Matrix B, Matrix A)
static Matrix	MG1_pi.mg1_pi(Matrix B, Matrix A, MG1PiOptions options)
static Matrix	MG1_ETAQA.mg1_pi_etaqa(Matrix B, Matrix A)
static Matrix	MG1_ETAQA.mg1_pi_etaqa(Matrix B, Matrix A, Matrix G)
static Matrix	MG1_ETAQA.mg1_pi_etaqa(Matrix B, Matrix A, Matrix G, Matrix C0)	Computes the aggregated stationary probability vector for an M/G/1-type Markov chain using the ETAQA method.
static double	MG1_ETAQA.mg1_qlen_etaqa(Matrix B, Matrix A, Matrix pi, int n)	Computes the n-th moment of queue length using ETAQA.
static Quadruple<Matrix,Double,Double,Matrix>	MG1_Shifts.mg1_shifts(Matrix A)
static Quadruple<Matrix,Double,Double,Matrix>	MG1_Shifts.mg1_shifts(Matrix A, String shiftType)	Applies the shift technique to an M/G/1-type block matrix.
static Matrix	NSF_GHT.nsfGht(Matrix A, int N)
static Matrix	NSF_GHT.nsfGht(Matrix A, int N, NSFGHTOptions options)	Gail-Hantler-Taylor algorithm for Non-Skip-Free Markov chains.
static Matrix	NSF_GHT.nsfPi(Matrix B, Matrix A, Matrix G)
static Matrix	NSF_GHT.nsfPi(Matrix B, Matrix A, Matrix G, NSFPiOptions options)	NSF_pi - Stationary vector of a Non-Skip-Free Markov chain.
static double	QBD_CAUDAL.QBD_CAUDAL(Matrix A0, Matrix A1, Matrix A2)
static double	QBD_CAUDAL.QBD_CAUDAL(Matrix A0, Matrix A1, Matrix A2, boolean Dual)
static Map<String,Matrix>	QBD_CR.QBD_CR(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_EG.QBD_EG(Matrix A0, Matrix A1, Matrix A2, boolean optVerbose)
static Map<String,Matrix>	QBD_FI.QBD_FI(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Matrix StartValue_, Integer RAPComp_)
static Map<String,Matrix>	QBD_IS.QBD_IS(Matrix A0, Matrix A1, Matrix A2, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_LR.QBD_LR(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Map<String,Matrix>	QBD_NI.QBD_NI(Matrix A0, Matrix A1, Matrix A2, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)
static Matrix	QBD_NI_Sylvest.QBD_NI_Sylvest(Matrix A, Matrix B, Matrix C, Matrix D)	Solves the Sylvester equation AXB + CX = D using complex Schur and Hessenberg-triangular decomposition.
static void	QBD_ParsePara.QBD_ParsePara(Matrix A0, Matrix A1, Matrix A2)
static Matrix	QBD_pi.QBD_pi(Matrix B0, Matrix B1, Matrix R)	QBD_pi: Stationary vector of a Quasi-Birth-Death Markov Chains [Neuts]
static Matrix	QBD_pi.QBD_pi(Matrix B0, Matrix B1, Matrix R, int MaxNumComp, int Verbose, Matrix Boundary, int RAPComp)
static void	QBD_RAP_ParsePara.QBD_RAP_ParsePara(Matrix A0, Matrix A1, Matrix A2)	QBD_RAP_ParsePara checks the validity of the input matrices A0, A1 and A2 for a QBD with RAP components.
static Map<String,Matrix>	QBD_CR.solve(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Integer RAPComp_)	Convenience alias for callers that expect a solve(...) entry point on the QBD_CR class.
static Map<String,Matrix>	QBD_FI.solve(Matrix A0arg, Matrix A1arg, Matrix A2arg, Integer MaxNumIt_, Integer Verbose_, String Mode_, Matrix StartValue_, Integer RAPComp_)	Convenience alias for callers that expect a solve(...) entry point on the QBD_FI class.
static Matrix	Stat.stat(Matrix A)

Constructors in jline.lib.smc with parameters of type Matrix

Modifier	Constructor	Description
	ETAQAResult(Matrix pi, Matrix G)
	GIM1CaudalResult(double eta, Matrix v)
	GIM1PiOptions(Matrix boundary, int maxNumComp, int verbose)
	MG1DecayResult(double eta, Matrix uT)
	MG1FIOptions(String mode, int maxNumIt, int verbose, String shiftType, Matrix startValue, int[] nonZeroBlocks)
	MG1PiOptions(Matrix boundary, int maxNumComp, int precision, String solver, boolean verbose, String mode)

Uses of Matrix in jline.solvers

Fields in jline.solvers declared as Matrix

Modifier and Type	Field	Description
Matrix	SolverResult.AN	Mean arrival rates [stations x classes]
Matrix	SolverResult.ANfcr	FCR mean arrival rates (attempted entries) [regions x classes]
Matrix	SolverResult.CN	Mean system response times [1 x chains]
Matrix[][]	SolverResult.CNt	Transient system response times [time_points][1 x chains]
Matrix	SolverOptions.cutoff	Cutoff threshold for numerical computations.
Matrix	SolverOptions.init_sol	Initial solution for iterative solvers
Matrix	SolverResult.pi_t	Transient probability distributions over time
Matrix	LayeredSolverResult.PN	Mean processor utilization [processors x 1]
Matrix	SolverResult.QN	Mean queue lengths [stations x classes]
Matrix	SolverResult.QNfcr	FCR mean queue lengths (jobs waiting at ingress) [regions x classes]
Matrix[][]	SolverResult.QNt	Transient queue lengths [time_points][stations x classes].
Matrix	LayeredSolverResult.rawEdgesWaiting	Waiting time by call edge [calls x 1]
Matrix	LayeredSolverResult.rawPhase1ServiceTime	Phase 1 service time by node [nodes x 1]
Matrix	LayeredSolverResult.rawPhase1Utilization	Phase 1 utilization by node [nodes x 1]
Matrix	LayeredSolverResult.rawPhase2ServiceTime	Phase 2 service time by node [nodes x 1]
Matrix	LayeredSolverResult.rawPhase2Utilization	Phase 2 utilization by node [nodes x 1]
Matrix	LayeredSolverResult.rawProcUtilization	Processor utilization by node [nodes x 1]
Matrix	LayeredSolverResult.rawProcWaiting	Processor waiting time by node [nodes x 1]
Matrix	LayeredSolverResult.rawThroughput	Throughput by node [nodes x 1]
Matrix	LayeredSolverResult.rawUtilization	Raw utilization by node [nodes x 1]
Matrix	SolverResult.RN	Mean response times [stations x classes]
Matrix	SolverResult.RNfcr	FCR mean response times (wait time at ingress) [regions x classes]
Matrix[][]	SolverResult.RNt	Transient response times [time_points][stations x classes]
Matrix	LayeredSolverResult.SN	Mean service time [tasks x 1]
Matrix	SolverResult.SS	Steady-state probability distribution
Matrix	SolverResult.SysTardN	Mean system tardiness [1 x classes]
Matrix	SolverResult.t	Time points for transient analysis
Matrix	SolverResult.TardN	Mean tardiness [stations x classes]
Matrix	SolverResult.TN	Mean throughputs [stations x classes]
Matrix	SolverResult.TNfcr	FCR mean throughputs (entry rate) [regions x classes]
Matrix[][]	SolverResult.TNt	Transient throughputs [time_points][stations x classes]
Matrix	SolverResult.UN	Mean server utilizations [stations x classes]
Matrix	SolverResult.UNfcr	FCR mean utilizations (capacity utilization) [regions x classes]
Matrix[][]	SolverResult.UNt	Transient utilizations [time_points][stations x classes]
Matrix	SolverResult.WN	Mean residence times [stations x classes]
Matrix	SolverResult.WNfcr	FCR mean residence times [regions x classes]
Matrix	SolverResult.XN	Mean system throughputs [1 x chains]
Matrix[][]	SolverResult.XNt	Transient system throughputs [time_points][1 x chains]

Methods in jline.solvers that return Matrix

Modifier and Type	Method	Description
Matrix	NetworkSolver.avgArvR()
Matrix	NetworkSolver.avgArvRChain()
Matrix	NetworkSolver.avgNodeArvRChain()
Matrix	NetworkSolver.avgNodeQLenChain()
Matrix	NetworkSolver.avgNodeResidTChain()
Matrix	NetworkSolver.avgNodeRespTChain()
Matrix	NetworkSolver.avgNodeTputChain()
Matrix	NetworkSolver.avgNodeUtilChain()
Matrix	NetworkSolver.avgQLen()
Matrix	NetworkSolver.avgQLenChain()
Matrix	NetworkSolver.avgResidT()
Matrix	NetworkSolver.avgResidTChain()
Matrix	NetworkSolver.avgRespT()
Matrix	NetworkSolver.avgRespTChain()
Matrix	NetworkSolver.avgSysRespT()
Matrix	NetworkSolver.avgSysTput()
Matrix	NetworkSolver.avgTput()
Matrix	NetworkSolver.avgTputChain()
Matrix	NetworkSolver.avgUtil()
Matrix	NetworkSolver.avgUtilChain()
Matrix	NetworkSolver.avgWaitT()
Matrix	NetworkSolver.getAvgArvR()	Computes and returns average arrival rates at steady-state.
Matrix	NetworkSolver.getAvgArvRChain()	Returns average arrival rates aggregated by job chains.
Matrix	NetworkSolver.getAvgNodeArvRChain()	Returns average node arrival rates aggregated by job chains.
Matrix	NetworkSolver.getAvgNodeQLenChain()	Returns average node queue lengths aggregated by job chains.
Matrix	NetworkSolver.getAvgNodeResidTChain()	Returns average node residence times aggregated by job chains.
Matrix	NetworkSolver.getAvgNodeRespTChain()	Returns average node response times aggregated by job chains.
Matrix	NetworkSolver.getAvgNodeTputChain()	Returns average node throughputs aggregated by job chains.
Matrix	NetworkSolver.getAvgNodeUtilChain()	Returns average node utilizations aggregated by job chains.
Matrix	NetworkSolver.getAvgQLen()	Computes and returns average queue lengths at steady-state.
Matrix	NetworkSolver.getAvgQLenChain()	Returns average queue lengths aggregated by job chains.
Matrix	NetworkSolver.getAvgResidT()	Computes and returns average residence times in queue (including service).
Matrix	NetworkSolver.getAvgResidTChain()	Returns average residence times aggregated by job chains.
Matrix	NetworkSolver.getAvgRespT()	Computes and returns average response times at steady-state.
Matrix	NetworkSolver.getAvgRespTChain()	Returns average response times aggregated by job chains.
Matrix	NetworkSolver.getAvgSysRespT()	Returns average system response times at steady state.
Matrix	NetworkSolver.getAvgSysTput()	Returns average system throughputs at steady state.
Matrix	NetworkSolver.getAvgTput()	Computes and returns average throughputs at steady-state.
Matrix	NetworkSolver.getAvgTputChain()	Returns average throughputs aggregated by job chains.
Matrix	NetworkSolver.getAvgUtil()	Computes and returns average server utilizations at steady-state.
Matrix	NetworkSolver.getAvgUtilChain()	Returns average server utilizations aggregated by job chains.
Matrix	NetworkSolver.getAvgWaitT()	Computes and returns average waiting times in queue excluding service time.
Matrix	SolverOptions.getCutoffMatrix(int nstations, int nclasses)	Ensures the cutoff is properly dimensioned for the given network structure.
Matrix	AvgTable.getData()	Returns the underlying matrix data.
Matrix	AvgTable.toMatrix()	Returns the table data as a Matrix after sanitizing numerical values.

Methods in jline.solvers with parameters of type Matrix

Modifier and Type	Method	Description
SolverOptions	SolverOptions.cutoff(Matrix cutoffMatrix)	Sets the numerical cutoff threshold as a matrix (builder pattern).
Ret.ProbabilityResult	NetworkSolver.getProb(int node, Matrix state)	Returns marginal state probabilities for a specific node and state.
Ret.ProbabilityResult	NetworkSolver.getProbAggr(int node, Matrix state_a)	Probability of a SPECIFIC per-class job distribution at a station.
Ret.ProbabilityResult	NetworkSolver.getProbMarg(int node, int jobclass, Matrix state_m)	Probability distribution for queue length of a SINGLE class at a station.
Ret.ProbabilityResult	NetworkSolver.prob(int node, Matrix state_a)
Ret.ProbabilityResult	NetworkSolver.probAggr(int node, Matrix state_a)
Ret.ProbabilityResult	NetworkSolver.probMarg(int node, int jobclass, Matrix state_m)
void	NetworkSolver.setAvgResults(Matrix Q, Matrix U, Matrix R, Matrix T, Matrix A, Matrix W, Matrix C, Matrix X, double runtime, String method, int iter)	Stores computed average metrics at steady-state in the solver result.
protected final void	NetworkSolver.setDistribResults(Matrix RD, double runtime)	Stores distribution metrics at steady-state.
void	NetworkSolver.setTranAvgResults(Matrix[][] Qt, Matrix[][] Ut, Matrix[][] Rt, Matrix[][] Tt, Matrix[][] Ct, Matrix[][] Xt, double runtimet)	Stores computed transient average metrics.
protected final void	NetworkSolver.setTranProb(Matrix t, Matrix pi_t, Matrix SS, double runtimet)	Stores transient probability distributions.

Constructors in jline.solvers with parameters of type Matrix

Modifier	Constructor	Description
	AvgTable(Matrix table)	Constructs an AvgTable from a Matrix.

Uses of Matrix in jline.solvers.auto

Methods in jline.solvers.auto that return Matrix

Modifier and Type	Method	Description
Matrix	SolverAUTO.avgArvR()	Alias for getAvgArvR()
Matrix	SolverAUTO.avgArvRChain()	Alias for getAvgArvRChain()
Matrix	SolverAUTO.avgQLen()	Alias for getAvgQLen()
Matrix	SolverAUTO.avgQLenChain()	Alias for getAvgQLenChain()
Matrix	SolverAUTO.avgResidT()	Alias for getAvgResidT()
Matrix	SolverAUTO.avgResidTChain()	Alias for getAvgResidTChain()
Matrix	SolverAUTO.avgRespT()	Alias for getAvgRespT()
Matrix	SolverAUTO.avgRespTChain()	Alias for getAvgRespTChain()
Matrix	SolverAUTO.avgSysRespT()	Alias for getAvgSysRespT()
Matrix	SolverAUTO.avgSysTput()	Alias for getAvgSysTput()
Matrix	SolverAUTO.avgTput()	Alias for getAvgTput()
Matrix	SolverAUTO.avgTputChain()	Alias for getAvgTputChain()
Matrix	SolverAUTO.avgUtil()	Alias for getAvgUtil()
Matrix	SolverAUTO.avgUtilChain()	Alias for getAvgUtilChain()
Matrix	SolverAUTO.avgWaitT()	Alias for getAvgWaitT()
Matrix	SolverAUTO.getAvgArvR()	Get average arrival rates at steady-state
Matrix	SolverAUTO.getAvgArvRChain()
Matrix	SolverAUTO.getAvgNodeArvRChain()	Get average node arrival rate by chain
Matrix	SolverAUTO.getAvgNodeQLenChain()	Get average node queue length by chain
Matrix	SolverAUTO.getAvgNodeResidTChain()	Get average node residence time by chain
Matrix	SolverAUTO.getAvgNodeRespTChain()	Get average node response time by chain
Matrix	SolverAUTO.getAvgNodeTputChain()	Get average node throughput by chain
Matrix	SolverAUTO.getAvgNodeUtilChain()	Get average node utilization by chain
Matrix	SolverAUTO.getAvgQLen()	Get average queue lengths at steady-state
Matrix	SolverAUTO.getAvgQLenChain()
Matrix	SolverAUTO.getAvgResidT()	Get average residence times at steady-state
Matrix	SolverAUTO.getAvgResidTChain()	Get average residence time by chain
Matrix	SolverAUTO.getAvgRespT()	Get average response times at steady-state
Matrix	SolverAUTO.getAvgRespTChain()
Matrix	SolverAUTO.getAvgSysRespT()
Matrix	SolverAUTO.getAvgSysTput()
Matrix	SolverAUTO.getAvgTput()	Get average throughputs at steady-state
Matrix	SolverAUTO.getAvgTputChain()
Matrix	SolverAUTO.getAvgUtil()	Get average utilizations at steady-state
Matrix	SolverAUTO.getAvgUtilChain()
Matrix	SolverAUTO.getAvgWaitT()	Get average waiting times (queue time excluding service)
Matrix	SolverAUTO.getPerctRespT(double[] percentiles)	Get response time percentiles
Matrix[]	SolverAUTO.getTranProb(Node node)
Matrix[]	SolverAUTO.getTranProbAggr(Node node)
Matrix[]	SolverAUTO.getTranProbSys()
Matrix[]	SolverAUTO.getTranProbSysAggr()
Matrix	SolverAUTO.perctRespT(double[] percentiles)	Alias for getPerctRespT()

Methods in jline.solvers.auto with parameters of type Matrix

Modifier and Type	Method	Description
double	SolverAUTO.getProb(Node node, Matrix state)
double	SolverAUTO.getProbAggr(Node node, Matrix state_a)
double	SolverAUTO.getProbMarg(Node node, int jobclass, Matrix state_m)	Get marginalized state probability
double	SolverAUTO.prob(Node node, Matrix state)	Alias for getProb()
double	SolverAUTO.probAggr(Node node, Matrix state_a)	Alias for getProbAggr()
double	SolverAUTO.probMarg(Node node, int jobclass, Matrix state_m)	Alias for getProbMarg()

Uses of Matrix in jline.solvers.ctmc

Fields in jline.solvers.ctmc declared as Matrix

Modifier and Type	Field	Description
Matrix	SolverCTMC.AnalyzerResult.CN
Matrix	SolverCTMC.TransientResult.CNt
Matrix	CTMCResult.infGen
Matrix	SolverCTMC.generatorResult.infGen
Matrix	SolverCTMC.AnalyzerResult.InfGen
Matrix	SolverCTMC.TransientResult.InfGen
Matrix	CTMCResult.Prob.joint
Matrix	CTMCResult.Prob.marginal
Matrix	CTMCResult.TranProbAggrResult.pit
Matrix	CTMCResult.TranProbResult.pit
Matrix	CTMCResult.TranProbSysAggrResult.pit
Matrix	CTMCResult.TranProbSysResult.pit
Matrix	SolverCTMC.TransientResult.pit
Matrix	SolverCTMC.StochCompResult.Q11
Matrix	SolverCTMC.StochCompResult.Q12
Matrix	SolverCTMC.StochCompResult.Q21
Matrix	SolverCTMC.StochCompResult.Q22
Matrix	SolverCTMC.AnalyzerResult.QN
Matrix	SolverCTMC.TransientResult.QNt
Matrix	SolverCTMC.AnalyzerResult.RN
Matrix	SolverCTMC.TransientResult.RNt
Matrix	SolverCTMC.StochCompResult.S
Matrix	CTMCResult.solverSpecific
Matrix	CTMCResult.space
Matrix	CTMCResult.spaceAggr
Matrix	SolverCTMC.SampleResult.state
Matrix	SolverCTMC.SampleSysResult.state
Matrix	CTMCResult.TranProbResult.stateSpace
Matrix	CTMCResult.TranProbSysResult.stateSpace
protected Matrix	ResultCTMC.stateSpace
Matrix	SolverCTMC.StateSpace.stateSpace
Matrix	SolverCTMC.AnalyzerResult.StateSpace
Matrix	SolverCTMC.TransientResult.StateSpace
Matrix	CTMCResult.TranProbSysAggrResult.stateSpaceAggr
Matrix	SolverCTMC.AnalyzerResult.StateSpaceAggr
Matrix	SolverCTMC.TransientResult.StateSpaceAggr
Matrix	CTMCResult.TranProbAggrResult.t
Matrix	CTMCResult.TranProbResult.t
Matrix	CTMCResult.TranProbSysAggrResult.t
Matrix	CTMCResult.TranProbSysResult.t
Matrix	SolverCTMC.SampleResult.t
Matrix	SolverCTMC.SampleSysResult.t
Matrix	SolverCTMC.TransientResult.t
Matrix	SolverCTMC.StochCompResult.T
Matrix	SolverCTMC.AnalyzerResult.TN
Matrix	SolverCTMC.TransientResult.TNt
Matrix	SolverCTMC.AnalyzerResult.UN
Matrix	SolverCTMC.TransientResult.UNt
Matrix	SolverCTMC.AnalyzerResult.XN
Matrix	SolverCTMC.TransientResult.XNt

Fields in jline.solvers.ctmc with type parameters of type Matrix

Modifier and Type	Field	Description
Map<StatefulNode,Matrix>	CTMCResult.nodeSpace
Map<Integer,Map<Integer,Matrix>>	CTMCResult.AVG.Q
Map<Integer,Map<Integer,Matrix>>	CTMCResult.AVG.T
Map<Integer,Map<Integer,Matrix>>	CTMCResult.AVG.U

Methods in jline.solvers.ctmc that return Matrix

Modifier and Type	Method	Description
Matrix	SolverCTMC.getCdfRespT(Matrix R)	Get the cumulative distribution function of response times using tagged job methodology
Matrix	SolverCTMC.getCdfSysRespT()	Get the cumulative distribution function of system response times
Matrix	ResultCTMCMargAggr.getPi()	Get the steady-state distribution
Matrix	ResultCTMCMargAggr.getPnir()	Get the marginal probabilities at stations
Matrix	SolverCTMC.SolverCtmcJointResult.getPnir()
Matrix	ResultCTMC.getQ()
Matrix	SolverCTMC.getRewardValueFunction(String rewardName)	Get the value function for a specific reward.
Matrix	ResultCTMC.getStateSpace()
Matrix	SolverCTMC.CtmcSsgResult.getStateSpace()
Matrix	ResultCTMC.getStateSpaceAggr()
Matrix	SolverCTMC.CtmcSsgResult.getStateSpaceAggr()
Matrix	SolverCTMC.getStateSpaceAggr()
Matrix	SolverCTMC.CtmcSsgResult.getStateSpaceHashed()

Methods in jline.solvers.ctmc with parameters of type Matrix

Modifier and Type	Method	Description
Matrix	SolverCTMC.getCdfRespT(Matrix R)	Get the cumulative distribution function of response times using tagged job methodology
Ret.ProbabilityResult	SolverCTMC.getProb(int node, Matrix state)
Ret.ProbabilityResult	SolverCTMC.getProb(StatefulNode node, Matrix state)
Ret.ProbabilityResult	SolverCTMC.getProbAggr(int node, Matrix state_a)
Ret.ProbabilityResult	SolverCTMC.getProbAggr(Node node, Matrix state_a)
Ret.ProbabilityResult	SolverCTMC.getProbAggr(StatefulNode node, Matrix state_a)
static void	SolverCTMC.printEventFilt(MatrixCell eventFilt, Matrix SS)
static void	SolverCTMC.printInfGen(Matrix Q, Matrix SS)

Constructors in jline.solvers.ctmc with parameters of type Matrix

Modifier	Constructor	Description
	AnalyzerResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Matrix InfGen, Matrix StateSpace, Matrix StateSpaceAggr, MatrixCell EventFiltration, double runtime, String fname, NetworkStruct sncopy)
	CtmcSsgResult(Matrix stateSpace, Matrix stateSpaceAggr, Matrix stateSpaceHashed, Map<StatefulNode,Matrix> nodeStateSpace, NetworkStruct sn)
	generatorResult(Matrix infGen, MatrixCell eventFilt, Map<Integer,Sync> ev)
	ResultCTMC(Matrix q, Matrix stateSpace, Matrix stateSpaceAggr, MatrixCell dfilt, double[][][] arvRates, double[][][] depRates, NetworkStruct sn)
	ResultCTMCMargAggr(Matrix Pnir, Matrix pi, double runtime, String fname)
	SolverCtmcJointResult(Matrix pnir, double runtime, String fname)
	StateSpace(Matrix stateSpace, MatrixCell localStateSpace)
	StochCompResult(Matrix S, Matrix Q11, Matrix Q12, Matrix Q21, Matrix Q22, Matrix T)
	TransientResult(Matrix t, Matrix pit, Matrix QNt, Matrix UNt, Matrix RNt, Matrix TNt, Matrix CNt, Matrix XNt, Matrix InfGen, Matrix StateSpace, Matrix StateSpaceAggr, MatrixCell EventFiltration, double runtime, String fname)

Constructor parameters in jline.solvers.ctmc with type arguments of type Matrix

Modifier	Constructor	Description
	CtmcSsgResult(Matrix stateSpace, Matrix stateSpaceAggr, Matrix stateSpaceHashed, Map<StatefulNode,Matrix> nodeStateSpace, NetworkStruct sn)

Uses of Matrix in jline.solvers.ctmc.analyzers

Methods in jline.solvers.ctmc.analyzers that return Matrix

Modifier and Type	Method	Description
Matrix	RewardResult.getStateSpace()

Methods in jline.solvers.ctmc.analyzers that return types with arguments of type Matrix

Modifier and Type	Method	Description
Map<String,Matrix>	RewardResult.getValueFunction()

Constructors in jline.solvers.ctmc.analyzers with parameters of type Matrix

Modifier	Constructor	Description
	RewardResult(Map<String,Matrix> valueFunction, double[] time, List<String> rewardNames, Matrix stateSpace, Map<String,Double> steadyState, double runtime)

Constructor parameters in jline.solvers.ctmc.analyzers with type arguments of type Matrix

Modifier	Constructor	Description
	RewardResult(Map<String,Matrix> valueFunction, double[] time, List<String> rewardNames, Matrix stateSpace, Map<String,Double> steadyState, double runtime)

Uses of Matrix in jline.solvers.ctmc.handlers

Methods in jline.solvers.ctmc.handlers that return Matrix

Modifier and Type	Method	Description
static Matrix	Solver_ctmc_marg.solver_ctmc_marg(NetworkStruct sn, SolverOptions options)

Uses of Matrix in jline.solvers.env

Fields in jline.solvers.env declared as Matrix

Modifier and Type	Field	Description
Matrix	SolverENV.SamplePathResult.SamplePathSegment.finalQ
Matrix	SolverENV.SamplePathResult.SamplePathSegment.finalT
Matrix	SolverENV.SamplePathResult.SamplePathSegment.finalU
Matrix	SolverENV.SamplePathResult.SamplePathSegment.initialQ
Matrix	SolverENV.SamplePathResult.SamplePathSegment.initialT
Matrix	SolverENV.SamplePathResult.SamplePathSegment.initialU
Matrix[][]	SolverENV.SamplePathResult.SamplePathSegment.QNt
Matrix[][]	SolverENV.EnvGeneratorResult.renvEventFilt
Matrix	SolverENV.EnvGeneratorResult.renvInfGen
Matrix[]	SolverENV.EnvGeneratorResult.stageInfGen
Matrix	SolverENV.SamplePathResult.SamplePathSegment.t
Matrix[][]	SolverENV.SamplePathResult.SamplePathSegment.TNt
Matrix[][]	SolverENV.SamplePathResult.SamplePathSegment.UNt

Methods in jline.solvers.env with parameters of type Matrix

Modifier and Type	Method	Description
static jline.solvers.env.SolverENV.Compression_result	SolverENV.ctmc_courtois(Matrix Q, MatrixCell MS)
static jline.solvers.env.SolverENV.Compression_result	SolverENV.ctmc_courtois(Matrix Q, MatrixCell MS, double q)
static jline.solvers.env.SolverENV.Compression_result	SolverENV.ctmc_decompose(Matrix Q, MatrixCell MS, SolverOptions options)	Perform CTMC decomposition using the configured method.

Constructors in jline.solvers.env with parameters of type Matrix

Modifier	Constructor	Description
	EnvGeneratorResult(Matrix[] stageInfGen, Matrix renvInfGen, MatrixCell[] stageEventFilt, Matrix[][] renvEventFilt, Map<Integer,Sync>[] stageEvents, List<RenvEvent> renvEvents)
	RenvEvent(int nodeIdx, int jobclassIdx, double prob, Matrix state, double t, double job, Pair<Integer,Integer> envTransition)

Uses of Matrix in jline.solvers.fluid

Fields in jline.solvers.fluid declared as Matrix

Modifier and Type	Field	Description
Matrix[][]	FluidResult.distribC	Distribution matrices for response time and passage time CDFs [stations][classes]
Matrix	FluidResult.hitProb	Cache hit probabilities [nodes x classes] from cacheqn analysis
Matrix	FluidResult.missProb	Cache miss probabilities [nodes x classes] from cacheqn analysis
Matrix	FluidResult.odeStateVec	ODE state vector solution from fluid approximation

Methods in jline.solvers.fluid that return Matrix

Modifier and Type	Method	Description
Matrix[]	SolverFluid.getCdfAoI()	Get CDF of Age of Information with automatic time range.
Matrix[]	SolverFluid.getCdfAoI(Matrix tValues)	Get CDF of Age of Information.

Methods in jline.solvers.fluid with parameters of type Matrix

Modifier and Type	Method	Description
Matrix[]	SolverFluid.getCdfAoI(Matrix tValues)	Get CDF of Age of Information.
void	SolverFluid.setFluidDistribResults(Matrix RD, double runtime)	Set distribution results with enhanced metadata for fluid solver
void	SolverFluid.setFluidTranAvgResults(Matrix[][] Qt, Matrix[][] Ut, Matrix[][] Rt, Matrix[][] Tt, Matrix[][] Ct, Matrix[][] Xt, double runtimet)	Set transient average results with proper validation

Uses of Matrix in jline.solvers.fluid.analyzers

Fields in jline.solvers.fluid.analyzers declared as Matrix

Modifier and Type	Field	Description
Matrix	ClosingAndStateDepMethodsAnalyzer.xvec_it
Matrix	MatrixMethodAnalyzer.xvec_it
Matrix	ClosingAndStateDepMethodsAnalyzer.xvec_t
Matrix	MatrixMethodAnalyzer.xvec_t

Methods in jline.solvers.fluid.analyzers that return Matrix

Modifier and Type	Method	Description
Matrix	ClosingAndStateDepMethodsAnalyzer.getXVecIt()
Matrix	FluidAnalyzer.getXVecIt()
Matrix	MatrixMethodAnalyzer.getXVecIt()
Matrix	MFQAnalyzer.getXVecIt()
Matrix	RMFAnalyzer.getXVecIt()

Methods in jline.solvers.fluid.analyzers with parameters of type Matrix

Modifier and Type	Method	Description
boolean	ClosingAndStateDepMethodsAnalyzer.detectStiffnessUsingOstrowski(NetworkStruct sn, Matrix rate)

Uses of Matrix in jline.solvers.fluid.handlers

Fields in jline.solvers.fluid.handlers declared as Matrix

Modifier and Type	Field	Description
Matrix	ImmediateElimination.EliminationResult.allJumpsReduced
Matrix	ImmediateElimination.EliminationResult.eventIdxReduced
Matrix	ImmediateElimination.EliminationResult.rateBaseReduced
Matrix	MethodStepHandler.tVec
Matrix	TransientDataHandler.tVec	Time vector storing integration time points
Matrix	MethodStepHandler.xVec
Matrix	TransientDataHandler.xVec	State vector matrix storing system state at each time point [time x dimensions]

Methods in jline.solvers.fluid.handlers that return Matrix

Modifier and Type	Method	Description
Matrix	PStarSearcher.generateTargetQueueLengths(Network model)

Methods in jline.solvers.fluid.handlers with parameters of type Matrix

Modifier and Type	Method	Description
static ImmediateElimination.EliminationResult	ImmediateElimination.eliminateImmediate(Matrix allJumps, Matrix rateBase, Matrix eventIdx, NetworkStruct sn, SolverOptions options)	Eliminate immediate transitions from ODE system
org.apache.commons.math3.optim.PointValuePair	PStarSearcher.findPStarValues(Network model, Matrix targetQueueLengths)

Constructors in jline.solvers.fluid.handlers with parameters of type Matrix

Modifier	Constructor	Description
	ClosingAndStateDepMethodsODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options)
	ClosingAndStateDepMethodsODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options, int numDimensions)
	CMAESObjectiveFunction(Matrix targetQueueLengths, Network model, boolean stiff)
	EliminationResult(Matrix allJumpsReduced, Matrix rateBaseReduced, Matrix eventIdxReduced, int[] stateMap)
	MatrixMethodODE(Matrix W, Matrix SQ, Matrix S, Matrix Qa, Matrix ALambda, int numDimensions, boolean[] isSourceState)
	MatrixMethodODE(Matrix W, Matrix SQ, Matrix S, Matrix Qa, Matrix ALambda, int numDimensions, boolean[] isSourceState, NetworkStruct sn, List<Double> pStarValues)
	PassageTimeODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options)
	PassageTimeODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options, int numDimensions)
	PStarOptimisationFunction(Matrix QNSSA, Network model, boolean stiff)

Constructor parameters in jline.solvers.fluid.handlers with type arguments of type Matrix

Modifier	Constructor	Description
	ClosingAndStateDepMethodsODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options)
	ClosingAndStateDepMethodsODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options, int numDimensions)
	PassageTimeODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options)
	PassageTimeODE(NetworkStruct sn, Map<Station,Map<JobClass,Matrix>> mu, Map<Station,Map<JobClass,Matrix>> phi, Map<Station,Map<JobClass,MatrixCell>> proc, Matrix rt, Matrix S, SolverOptions options, int numDimensions)

Uses of Matrix in jline.solvers.jmt

Fields in jline.solvers.jmt declared as Matrix

Modifier and Type	Field	Description
Matrix	JMTResult.cacheAN	Cache node arrival rates [nnodes x nclasses].
Matrix	JMTResult.cacheTN	Cache node throughputs [nnodes x nclasses].
Matrix	JMTResult.TransientProbabilityResult.Pi_t
Matrix	JMTResult.TransientProbabilityResult.SSnode_a

Methods in jline.solvers.jmt that return Matrix

Modifier and Type	Method	Description
Matrix[][]	SolverJMT.getTranQLen()	Returns transient queue length results from the last getTranAvg() call.
Matrix[][]	SolverJMT.getTranTput()	Returns transient throughput results from the last getTranAvg() call.
Matrix[][]	SolverJMT.getTranUtil()	Returns transient utilization results from the last getTranAvg() call.

Methods in jline.solvers.jmt with parameters of type Matrix

Modifier and Type	Method	Description
double	SolverJMT.getProbAggr(Node node, Matrix state_a)

Constructors in jline.solvers.jmt with parameters of type Matrix

Modifier	Constructor	Description
	TransientProbabilityResult(Matrix Pi_t, Matrix SSnode_a)

Uses of Matrix in jline.solvers.jmt.io

Methods in jline.solvers.jmt.io that return Matrix

Modifier and Type	Method	Description
Matrix[][][]	JMTIO.parseLogs(boolean[] isNodeLogged, MetricType metric)	Parses JMT log files for the specified metric type.
Matrix[][]	JMTIO.parseTranRespT(List<String[]> arvData, List<String[]> depData)	Parses transient response time data from arrival and departure logs.

Methods in jline.solvers.jmt.io with parameters of type Matrix

Modifier and Type	Method	Description
Object[]	JMTIO.parseTranState(List<String[]> arvData, List<String[]> depData, Matrix nodePreload)	Parses transient state data from log files.

Uses of Matrix in jline.solvers.ldes

Fields in jline.solvers.ldes declared as Matrix

Modifier and Type	Field	Description
Matrix	LNLDESResult.ALN	Arrival rate per LQN element [1 x nidx]
Matrix	LDESResult.ANCI	Confidence interval half-widths for arrival rates [stations x classes]
Matrix	LDESResult.avgOrbitSize	Average orbit size (time-weighted mean jobs in orbit) [stations x classes]
Matrix	LDESResult.avgRenegingWaitTime	Average wait time before reneging [stations x classes]
Matrix	LDESResult.balkedCustomers	Number of customers who balked (refused to join upon arrival) [stations x classes]
Matrix	LDESResult.balkingProbability	Balking probability (balked / arrivals) [stations x classes]
Matrix	LNLDESResult.QLN	Queue length per LQN element [1 x nidx]
Matrix	LNLDESResult.QLNCI	Queue length confidence interval half-widths [1 x nidx]
Matrix	LDESResult.QNCI	Confidence interval half-widths for queue lengths [stations x classes]
Matrix	LDESResult.QNRelPrec	Relative precision achieved for queue lengths (CI half-width / mean) [stations x classes]
Matrix	LDESResult.QNSamples	Number of samples (observations) used for queue length estimation [stations x classes]
Matrix	LDESResult.renegedCustomers	Number of customers who reneged (abandoned queue due to expired patience) [stations x classes]
Matrix	LDESResult.renegingRate	Reneging rate (reneged / (completed + reneged + dropped)) [stations x classes]
Matrix	LDESResult.retrialDropped	Number of customers dropped after exceeding max retrial attempts [stations x classes]
Matrix	LDESResult.retriedCustomers	Number of successful retrial attempts (customers who re-entered queue from orbit) [stations x classes]
Matrix	LNLDESResult.RLN	Response time per LQN element [1 x nidx]
Matrix	LNLDESResult.RLNCI	Response time confidence interval half-widths [1 x nidx]
Matrix	LDESResult.RNCI	Confidence interval half-widths for response times [stations x classes]
Matrix	LDESResult.RNRelPrec	Relative precision achieved for response times (CI half-width / mean) [stations x classes]
Matrix	LDESResult.RNSamples	Number of samples (observations) used for response time estimation [stations x classes]
Matrix	LNLDESResult.TLN	Throughput per LQN element [1 x nidx]
Matrix	LNLDESResult.TLNCI	Throughput confidence interval half-widths [1 x nidx]
Matrix	LDESResult.TNCI	Confidence interval half-widths for throughputs [stations x classes]
Matrix	LDESResult.TNRelPrec	Relative precision achieved for throughputs (CI half-width / mean) [stations x classes]
Matrix	LDESResult.TNSamples	Number of samples (observations) used for throughput estimation [stations x classes]
Matrix	LDESResult.tranProbPit	Transient state probabilities over time [numTimePoints x numStates].
Matrix	LDESResult.tranProbStateSpace	Transient state space matrix [numStates x stateVectorLength].
Matrix	LDESResult.tranProbT	Time points for transient probability analysis.
Matrix	LDESResult.tranSync	Transient synchronization matrix for multi-class coordination
Matrix	LNLDESResult.ULN	Utilization per LQN element [1 x nidx]
Matrix	LNLDESResult.ULNCI	Utilization confidence interval half-widths [1 x nidx]
Matrix	LDESResult.UNCI	Confidence interval half-widths for utilizations [stations x classes]
Matrix	LDESResult.UNRelPrec	Relative precision achieved for utilizations (CI half-width / mean) [stations x classes]
Matrix	LDESResult.UNSamples	Number of samples (observations) used for utilization estimation [stations x classes]
Matrix	LNLDESResult.WLN	Residence/waiting time per LQN element [1 x nidx]
Matrix	LDESResult.WNCI	Confidence interval half-widths for residence times [stations x classes]

Fields in jline.solvers.ldes with type parameters of type Matrix

Modifier and Type	Field	Description
Map<Integer,Matrix>	LDESResult.tranProbAggrPit	Transient aggregated state probabilities per node [nodeIdx] -> [numTimePoints x numAggrStates].
Map<Integer,Matrix>	LDESResult.tranProbAggrStateSpace	Transient aggregated state space per node [nodeIdx] -> [numAggrStates x numClasses].
Map<Integer,Matrix>	LDESResult.tranSysState	Transient system state matrices indexed by time points

Methods in jline.solvers.ldes with parameters of type Matrix

Modifier and Type	Method	Description
Ret.ProbabilityResult	SolverLDES.getProb(int nodeIndex, Matrix state)	Estimates state probability using node index.
Ret.ProbabilityResult	SolverLDES.getProb(StatefulNode node, Matrix state)	Estimates the steady-state probability of a specific state at a node via LDES simulation.
Ret.ProbabilityResult	SolverLDES.getProbAggr(int nodeIndex, Matrix stateAggr)	Estimates aggregated state probability using node index.
Ret.ProbabilityResult	SolverLDES.getProbAggr(StatefulNode node, Matrix stateAggr)	Estimates the steady-state probability of a specific aggregated (per-class) state at a node.

Constructors in jline.solvers.ldes with parameters of type Matrix

Modifier	Constructor	Description
	LDESResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Map<Integer,Matrix> tranSysState, Matrix tranSync, NetworkStruct sn)	Constructs a LDESResult with the specified performance metrics and state information.

Constructor parameters in jline.solvers.ldes with type arguments of type Matrix

Modifier	Constructor	Description
	LDESResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Map<Integer,Matrix> tranSysState, Matrix tranSync, NetworkStruct sn)	Constructs a LDESResult with the specified performance metrics and state information.

Uses of Matrix in jline.solvers.ln

Fields in jline.solvers.ln declared as Matrix

Modifier and Type	Field	Description
Matrix	SolverLN.arvproc_classes_updmap
Matrix	SolverLN.call_classes_updmap
Matrix	SolverLN.callresidt
Matrix	SolverLN.LNState.callresidt
Matrix	SolverLN.callresidt_prev
Matrix	SolverLN.LNState.callresidtPrev
Matrix	SolverLN.callservt
Matrix	SolverLN.LNState.callservt
Matrix	SolverLN.callservt_prev
Matrix	SolverLN.LNState.callservtPrev
Matrix	SolverLN.ignore
Matrix	SolverLN.ilscaling
Matrix	SolverLN.LNState.ilscaling
Matrix	SolverLN.LNState.njobs
Matrix	SolverLN.njobs
Matrix	SolverLN.njobsorig
Matrix	SolverLN.prOvertake
Matrix	SolverLN.LNState.ptaskcallers
Matrix	SolverLN.ptaskcallers
Matrix	SolverLN.LNState.residt
Matrix	SolverLN.residt
Matrix	SolverLN.residt_prev
Matrix	SolverLN.LNState.residtPrev
Matrix	SolverLN.route_prob_updmap
Matrix	SolverLN.LNState.servt
Matrix	SolverLN.servt
Matrix	SolverLN.servt_classes_updmap
Matrix	SolverLN.servt_ph1
Matrix	SolverLN.servt_ph2
Matrix	SolverLN.servt_prev
Matrix	SolverLN.servtmatrix
Matrix	SolverLN.LNState.servtPrev
Matrix	SolverLN.LNState.thinkt
Matrix	SolverLN.thinkt
Matrix	SolverLN.thinkt_classes_updmap
Matrix	SolverLN.thinkt_prev
Matrix	SolverLN.LNState.thinktPrev
Matrix	SolverLN.LNState.tput
Matrix	SolverLN.tput
Matrix	SolverLN.tput_prev
Matrix	SolverLN.LNState.tputPrev
Matrix	SolverLN.unique_route_prob_updmap
Matrix	SolverLN.LNState.util
Matrix	SolverLN.util
Matrix	SolverLN.util_ph1
Matrix	SolverLN.util_ph2

Fields in jline.solvers.ln with type parameters of type Matrix

Modifier and Type	Field	Description
Map<Integer,Matrix>	SolverLN.callservtcdf
Map<Integer,Matrix>	SolverLN.ptaskcallers_step
Map<Integer,Matrix>	SolverLN.servtcdf

Methods in jline.solvers.ln that return Matrix

Modifier and Type	Method	Description
Matrix	SolverLN.getArvproc_classes_updmap()
Matrix	SolverLN.getCall_classes_updmap()
Matrix	SolverLN.getEntryServiceMatrix()
Matrix	SolverLN.getEntryServiceMatrixRecursion(LayeredNetworkStruct lqn, int aidx, int eidx, Matrix U)
Matrix	SolverLN.getRoute_prob_updmap()
Matrix	SolverLN.getServt_classes_updmap()
Matrix	SolverLN.getThinkt_classes_updmap()
Matrix	SolverLN.integerMapToMatrix(Map<Integer,List<Integer[]>> cell)

Methods in jline.solvers.ln with parameters of type Matrix

Modifier and Type	Method	Description
Matrix	SolverLN.getEntryServiceMatrixRecursion(LayeredNetworkStruct lqn, int aidx, int eidx, Matrix U)

Uses of Matrix in jline.solvers.mam

Fields in jline.solvers.mam declared as Matrix

Modifier and Type	Field	Description
Matrix	MAMResult.actionRates

Fields in jline.solvers.mam with type parameters of type Matrix

Modifier and Type	Field	Description
List<Matrix>	MAMResult.equilibrium
List<Matrix>	MAMResult.generators

Methods in jline.solvers.mam that return Matrix

Modifier and Type	Method	Description
Matrix	MAMFJResult.getQN()
Matrix	MAMFJResult.getRN()
Matrix	MAMFJResult.getTN()
Matrix	MAMFJResult.getUN()
Matrix	MAMFJResult.getXN()

Methods in jline.solvers.mam with parameters of type Matrix

Modifier and Type	Method	Description
Ret.ProbabilityResult	SolverMAM.getProbMarg(int node, int jobclass, Matrix state_m)	Get marginal queue-length probability distribution for a job class.

Constructors in jline.solvers.mam with parameters of type Matrix

Modifier	Constructor	Description
	MAMFJResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix XN, List<MainFJ.FJPercentileResult> percentileResults)

Uses of Matrix in jline.solvers.mam.handlers

Fields in jline.solvers.mam.handlers declared as Matrix

Modifier and Type	Field	Description
final Matrix	RCATModel.AP
final Matrix	MetricsResult.CN
final Matrix	BMAPMAP1Result.G	G matrix
final Matrix	BMAPMAP1Result.pi	Aggregated stationary probabilities [pi0, pi1, piStar]
final Matrix	MAPBMAP1Result.pi
final Matrix	RCATModel.processMap
final Matrix	MetricsResult.QN
final Matrix	MAPBMAP1Result.R
final Matrix[][]	RCATModel.R
final Matrix	MetricsResult.RN
final Matrix	MetricsResult.TN
final Matrix	MetricsResult.UN
final Matrix	INAPResult.x
final Matrix	MetricsResult.XN

Fields in jline.solvers.mam.handlers with type parameters of type Matrix

Modifier and Type	Field	Description
final List<Matrix>	INAPResult.pi
final List<Matrix>	INAPResult.Q

Methods in jline.solvers.mam.handlers that return Matrix

Modifier and Type	Method	Description
Matrix	INAPResult.component1()
Matrix	BMAPMAP1Result.component5()
Matrix	BMAPMAP1Result.component6()
Matrix	MetricsResult.getCN()
Matrix	BMAPMAP1Result.getG()
Matrix	BMAPMAP1Result.getPi()
Matrix	MetricsResult.getQN()
Matrix[][]	TransientResult.getQt()
Matrix	MetricsResult.getRN()
Matrix	MetricsResult.getTN()
Matrix[][]	TransientResult.getTt()
Matrix	MetricsResult.getUN()
Matrix[][]	TransientResult.getUt()
Matrix	INAPResult.getX()
Matrix	MetricsResult.getXN()

Methods in jline.solvers.mam.handlers that return types with arguments of type Matrix

Modifier and Type	Method	Description
List<Matrix>	INAPResult.component2()
List<Matrix>	INAPResult.component3()
List<Matrix>	INAPResult.getPi()
List<Matrix>	INAPResult.getQ()

Methods in jline.solvers.mam.handlers with parameters of type Matrix

Modifier and Type	Method	Description
static double	Qna_superpos.qna_superpos(Matrix lambda, Matrix a2)
static BMAPMAP1Result	Solver_mam_bmap_map_1.solver_mam_bmap_map_1(List<Matrix> D, Matrix S0, Matrix S1)
static BMAPMAP1Result	Solver_mam_bmap_map_1.solver_mam_bmap_map_1(List<Matrix> D, Matrix S0, Matrix S1, int nMoments)	Solves a BMAP/MAP/1 queue using M/G/1 type matrix-analytic methods.
static MAPBMAP1Result	Solver_mam_map_bmap_1.solver_mam_map_bmap_1(Matrix C0, Matrix C1, List<Matrix> D)

Method parameters in jline.solvers.mam.handlers with type arguments of type Matrix

Modifier and Type	Method	Description
static BMAPMAP1Result	Solver_mam_bmap_map_1.solver_mam_bmap_map_1(List<Matrix> D, Matrix S0, Matrix S1)
static BMAPMAP1Result	Solver_mam_bmap_map_1.solver_mam_bmap_map_1(List<Matrix> D, Matrix S0, Matrix S1, int nMoments)	Solves a BMAP/MAP/1 queue using M/G/1 type matrix-analytic methods.
static MAPBMAP1Result	Solver_mam_map_bmap_1.solver_mam_map_bmap_1(Matrix C0, Matrix C1, List<Matrix> D)

Constructors in jline.solvers.mam.handlers with parameters of type Matrix

Modifier	Constructor	Description
	BMAPMAP1Result(double meanQueueLength, double utilization, double meanResponseTime, double throughput, Matrix pi, Matrix G, double meanBatchSize)
	INAPResult(Matrix x, List<Matrix> pi, List<Matrix> Q, int iter)
	MAPBMAP1Result(double meanQueueLength, double utilization, double meanResponseTime, double throughput, Matrix pi, Matrix R, double meanBatchSize)
	MetricsResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN)
	RCATModel(Matrix[][] R, Matrix AP, Matrix processMap, List<ActionInfo> actionMap, int[] N)
	TransientResult(Matrix[][] Qt, Matrix[][] Ut, Matrix[][] Tt)

Constructor parameters in jline.solvers.mam.handlers with type arguments of type Matrix

Modifier	Constructor	Description
	INAPResult(Matrix x, List<Matrix> pi, List<Matrix> Q, int iter)

Uses of Matrix in jline.solvers.mva

Fields in jline.solvers.mva declared as Matrix

Modifier and Type	Field	Description
Matrix	MVAResult.hitProb	Cache hit probabilities [items x classes] (used by cache analyzers)
Matrix	MVAResult.missProb	Cache miss probabilities [items x classes] (used by cache analyzers)

Methods in jline.solvers.mva that return Matrix

Modifier and Type	Method	Description
Matrix	ProbabilityResult.getMarginal(int station, int jobclass)	Get the marginal probability distribution for a specific station and class.
Matrix	ProbabilityResult.getProbabilityVector()	Get the probability distribution vector.

Methods in jline.solvers.mva with parameters of type Matrix

Modifier and Type	Method	Description
Ret.ProbabilityResult	SolverMVA.getProbMarg(int ist, int jobclass, Matrix state_m)	Get marginalized state probabilities for a specific station and job class with state filter
void	ProbabilityResult.setMarginal(int station, int jobclass, Matrix probVector)	Set the marginal probability distribution for a specific station and class.

Constructors in jline.solvers.mva with parameters of type Matrix

Modifier	Constructor	Description
	ProbabilityResult(Matrix probabilityVector)	Constructor for probability distribution result.

Uses of Matrix in jline.solvers.mva.handlers

Methods in jline.solvers.mva.handlers that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Solver_amvald.solver_amvald_forward(List<Matrix> gamma, Matrix tau, Matrix Qchain_in, Matrix Xchain_in, Matrix Uchain_in, Matrix STchain_in, Matrix Vchain_in, Matrix Nchain_in, Matrix SCVchain_in, double Nt, double delta, Matrix deltaclass, List<Integer> ocl, List<Integer> ccl, List<Integer> nnzclasses, Map<Integer,List<Integer>> nnzclasses_eprio, Map<Integer,List<Integer>> nnzclasses_hprio, Map<Integer,List<Integer>> nnzclasses_ehprio, int M, int K, Matrix nservers, Matrix schedparam, Matrix lldscaling_in, Map<Station,SerializableFunction<Matrix,Double>> cdscaling, Map<Station,Matrix> ljdscaling, Map<Station,Matrix> ljdcutoffs, List<List<Matrix>> ljcdscaling, List<Matrix> ljcdcutoffs, List<SchedStrategy> sched, List<Station> stations, SolverOptions options)
static Pair<Matrix,Matrix>	Solver_amvald.solver_amvald_forward(List<Matrix> gamma, Matrix tau, Matrix Qchain_in, Matrix Xchain_in, Matrix Uchain_in, Matrix STchain_in, Matrix Vchain_in, Matrix Nchain_in, Matrix SCVchain_in, double Nt, double delta, Matrix deltaclass, List<Integer> ocl, List<Integer> ccl, List<Integer> nnzclasses, Map<Integer,List<Integer>> nnzclasses_eprio, Map<Integer,List<Integer>> nnzclasses_hprio, Map<Integer,List<Integer>> nnzclasses_ehprio, int M, int K, Matrix nservers, Matrix schedparam, Matrix lldscaling_in, Map<Station,SerializableFunction<Matrix,Double>> cdscaling, Map<Station,Matrix> ljdscaling, Map<Station,Matrix> ljdcutoffs, List<List<Matrix>> ljcdscaling, List<Matrix> ljcdcutoffs, List<SchedStrategy> sched, List<Station> stations, SolverOptions options)

Methods in jline.solvers.mva.handlers with parameters of type Matrix

Modifier and Type	Method	Description
static double	Solver_qna.qna_superpos(Matrix lambda, Matrix a2)
static Pair<Matrix,Matrix>	Solver_amvald.solver_amvald_forward(List<Matrix> gamma, Matrix tau, Matrix Qchain_in, Matrix Xchain_in, Matrix Uchain_in, Matrix STchain_in, Matrix Vchain_in, Matrix Nchain_in, Matrix SCVchain_in, double Nt, double delta, Matrix deltaclass, List<Integer> ocl, List<Integer> ccl, List<Integer> nnzclasses, Map<Integer,List<Integer>> nnzclasses_eprio, Map<Integer,List<Integer>> nnzclasses_hprio, Map<Integer,List<Integer>> nnzclasses_ehprio, int M, int K, Matrix nservers, Matrix schedparam, Matrix lldscaling_in, Map<Station,SerializableFunction<Matrix,Double>> cdscaling, Map<Station,Matrix> ljdscaling, Map<Station,Matrix> ljdcutoffs, List<List<Matrix>> ljcdscaling, List<Matrix> ljcdcutoffs, List<SchedStrategy> sched, List<Station> stations, SolverOptions options)

Method parameters in jline.solvers.mva.handlers with type arguments of type Matrix

Modifier and Type	Method	Description
static Pair<Matrix,Matrix>	Solver_amvald.solver_amvald_forward(List<Matrix> gamma, Matrix tau, Matrix Qchain_in, Matrix Xchain_in, Matrix Uchain_in, Matrix STchain_in, Matrix Vchain_in, Matrix Nchain_in, Matrix SCVchain_in, double Nt, double delta, Matrix deltaclass, List<Integer> ocl, List<Integer> ccl, List<Integer> nnzclasses, Map<Integer,List<Integer>> nnzclasses_eprio, Map<Integer,List<Integer>> nnzclasses_hprio, Map<Integer,List<Integer>> nnzclasses_ehprio, int M, int K, Matrix nservers, Matrix schedparam, Matrix lldscaling_in, Map<Station,SerializableFunction<Matrix,Double>> cdscaling, Map<Station,Matrix> ljdscaling, Map<Station,Matrix> ljdcutoffs, List<List<Matrix>> ljcdscaling, List<Matrix> ljcdcutoffs, List<SchedStrategy> sched, List<Station> stations, SolverOptions options)

Uses of Matrix in jline.solvers.nc

Fields in jline.solvers.nc declared as Matrix

Modifier and Type	Field	Description
Matrix	SolverNC.SolverNCLDReturn.C
Matrix	NCResult.hitProb
Matrix	SolverNC.SolverNCMargReturn.lPr
Matrix	NCResult.missProb
Matrix	NCResult.pij
Matrix	SolverNC.SolverNCLDReturn.Q
Matrix	SolverNC.SolverNCReturn.Q
Matrix	SolverNC.SolverNCLDReturn.R
Matrix	SolverNC.SolverNCReturn.R
Matrix	NCResult.STeff
Matrix	SolverNC.SolverNCReturn.STeff
Matrix	SolverNC.SolverNCLDReturn.T
Matrix	SolverNC.SolverNCReturn.T
Matrix	SolverNC.SolverNCLDReturn.U
Matrix	SolverNC.SolverNCReturn.U
Matrix	SolverNC.SolverNCLDReturn.X
Matrix	SolverNC.SolverNCReturn.X

Methods in jline.solvers.nc that return Matrix

Modifier and Type	Method	Description
Matrix	SolverNC.getCdfRespT(AvgHandle... R)	Get cumulative distribution function of response times at FCFS and delay nodes

Methods in jline.solvers.nc with parameters of type Matrix

Modifier and Type	Method	Description
Double	SolverNC.getProb(Node node, Matrix state)
Double	SolverNC.getProbAggr(Node node, Matrix state_a)	Get aggregated probability for a specific node and state

Constructors in jline.solvers.nc with parameters of type Matrix

Modifier	Constructor	Description
	SolverNCLDReturn(Matrix Q, Matrix U, Matrix R, Matrix T, Matrix C, Matrix X, double lG, double runtime, int it, String method)
	SolverNCMargReturn(Matrix lPr, double G, double lG, double runtime)
	SolverNCReturn(Matrix Q, Matrix U, Matrix R, Matrix T, int C, Matrix X, Double lG, Matrix STeff, int it, double runtime, String method)

Uses of Matrix in jline.solvers.qns

Methods in jline.solvers.qns with parameters of type Matrix

Modifier and Type	Method	Description
Ret.ProbabilityResult	SolverQNS.getProb(int node, Matrix state)
Ret.ProbabilityResult	SolverQNS.getProbAggr(int node, Matrix state_a)

Constructors in jline.solvers.qns with parameters of type Matrix

Modifier	Constructor	Description
	QNSResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix AN, Matrix WN, Matrix CN, Matrix XN, double runtime, String method, int iter)	Constructor with all parameters

Uses of Matrix in jline.solvers.ssa

Fields in jline.solvers.ssa declared as Matrix

Modifier and Type	Field	Description
Matrix	SSAResult.ANCI	Confidence interval half-widths for arrival rates [stations x classes]
final Matrix	SSAValues.pi
Matrix	SSAResult.QNCI	Confidence interval half-widths for queue lengths [stations x classes]
Matrix	SSAResult.RNCI	Confidence interval half-widths for response times [stations x classes]
final Matrix	SSAValues.SSq
Matrix	SampleNodeState.state	State information at each time point
Matrix	SampleNodeState.t	Time points of the sampling
Matrix	SampleSysState.t	Time points of the sampling
Matrix	SSAResult.TNCI	Confidence interval half-widths for throughputs [stations x classes]
Matrix	SSAResult.tranSync	Transient synchronization matrix for multi-class coordination
final Matrix	SSAValues.tranSync
Matrix	SSAResult.UNCI	Confidence interval half-widths for utilizations [stations x classes]
Matrix	SSAResult.WNCI	Confidence interval half-widths for residence times [stations x classes]

Fields in jline.solvers.ssa with type parameters of type Matrix

Modifier and Type	Field	Description
final Map<Integer,Matrix>	SSAValues.arvRates
final Map<Integer,Matrix>	SSAValues.depRates
Map<Station,Matrix>	SSAResult.space	State space matrices for each station in the network
List<Matrix>	SampleSysState.state	State information for each stateful node at each time point
Map<Integer,Matrix>	SSAResult.tranSysState	Transient system state matrices indexed by time points
final Map<Integer,Matrix>	SSAValues.tranSysState

Methods in jline.solvers.ssa with parameters of type Matrix

Modifier and Type	Method	Description
Ret.ProbabilityResult	SolverSSA.getProb(int node, Matrix state)	Get marginal probability for a specific node state (by node index).
double	SolverSSA.getProb(Node node, Matrix state)	Get probability for a specific node state
double	SolverSSA.getProbAggr(Node node, Matrix state)	Get aggregated probability for a specific node state

Constructors in jline.solvers.ssa with parameters of type Matrix

Modifier	Constructor	Description
	SampleNodeState(Node handle, Matrix t, Matrix state, List<Event> event, boolean isaggregate)
	SampleSysState(List<Node> handle, Matrix t, List<Matrix> state, List<Event> event, boolean isaggregate)
	SSAResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Map<Integer,Matrix> tranSysState, Matrix tranSync, NetworkStruct sn)	Constructs an SSAResult with the specified performance metrics and state information.
	SSAValues(Matrix pi, Matrix SSq, Map<Integer,Matrix> arvRates, Map<Integer,Matrix> depRates, Map<Integer,Matrix> tranSysState, Matrix tranSync, NetworkStruct sn)

Constructor parameters in jline.solvers.ssa with type arguments of type Matrix

Modifier	Constructor	Description
	SSAResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Map<Integer,Matrix> tranSysState, Matrix tranSync, NetworkStruct sn)	Constructs an SSAResult with the specified performance metrics and state information.
	SSAValues(Matrix pi, Matrix SSq, Map<Integer,Matrix> arvRates, Map<Integer,Matrix> depRates, Map<Integer,Matrix> tranSysState, Matrix tranSync, NetworkStruct sn)

Uses of Matrix in jline.solvers.ssa.analyzers

Method parameters in jline.solvers.ssa.analyzers with type arguments of type Matrix

Modifier and Type	Method	Description
static SSAResult	Solver_ssa_analyzer_nrm.solver_ssa_analyzer_nrm(NetworkStruct sn, Map<StatefulNode,Matrix> init_state, SolverOptions options)
static SSAResult	Solver_ssa_analyzer_parallel.solver_ssa_analyzer_parallel(NetworkStruct sn, Map<StatefulNode,Matrix> init_state, SolverOptions options, SolverSSA solverSSA)
static SSAResult	Solver_ssa_analyzer_serial.solver_ssa_analyzer_serial(NetworkStruct sn, boolean hash, Map<StatefulNode,Matrix> init_state, SolverOptions options, SolverSSA solverSSA)

Uses of Matrix in jline.solvers.ssa.handlers

Fields in jline.solvers.ssa.handlers declared as Matrix

Modifier and Type	Field	Description
final Matrix	SolverSSAResultNRM.CN
final Matrix	Solver_ssa_nrm_space.SolverSSAResultNRMSpace.depRates
final Matrix	Solver_ssa_nrm_space.SolverSSAResultNRMSpace.outspace
final Matrix	Solver_ssa_nrm_space.SolverSSAResultNRMSpace.pi
final Matrix	SolverSSAResultNRM.QN
final Matrix	SolverSSAResultNRM.RN
final Matrix	SolverSSAResultNRM.TN
final Matrix	SolverSSAResultNRM.UN
final Matrix	SolverSSAResultNRM.XN

Methods in jline.solvers.ssa.handlers that return Matrix

Modifier and Type	Method	Description
Matrix	SolverSSAResultNRM.getCN()
Matrix	SolverSSAResultNRM.getQN()
Matrix	SolverSSAResultNRM.getRN()
Matrix	SolverSSAResultNRM.getTN()
Matrix	SolverSSAResultNRM.getUN()
Matrix	SolverSSAResultNRM.getXN()

Methods in jline.solvers.ssa.handlers that return types with arguments of type Matrix

Modifier and Type	Method	Description
static Pair<List<Double>,Matrix>	Solver_ssa_nrm_space.next_reaction_method_space(Matrix S, List<List<Integer>> D, kotlin.jvm.functions.Function1<Matrix,Double>[] a, Matrix nvec0, int samples, SolverOptions options, Map<String,double[]> reactcache, kotlin.jvm.functions.Function1<Matrix,String> hashfun)
static kotlin.Triple<Matrix,Matrix,NetworkStruct>	Solver_ssa_reachability.solver_ssa_reachability(NetworkStruct sn, SolverOptions options)
static kotlin.Triple<Matrix,Matrix,NetworkStruct>	Solver_ssa_reachability.solver_ssa_reachability(NetworkStruct sn, SolverOptions options)

Methods in jline.solvers.ssa.handlers with parameters of type Matrix

Modifier and Type	Method	Description
static void	Solver_ssa_nrm.next_reaction_method_direct(Matrix S, List<Integer>[] D, Function<Matrix,Double>[] a, Matrix nvec0, int samples, SolverOptions options, Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, NetworkStruct sn, List<Integer> fromIdx, List<int[]> fromIR)
static Pair<List<Double>,Matrix>	Solver_ssa_nrm_space.next_reaction_method_space(Matrix S, List<List<Integer>> D, kotlin.jvm.functions.Function1<Matrix,Double>[] a, Matrix nvec0, int samples, SolverOptions options, Map<String,double[]> reactcache, kotlin.jvm.functions.Function1<Matrix,String> hashfun)
static void	Solver_ssa_findenabled.solver_ssa_findenabled(NetworkStruct sn, EventCache eventCache, int A, Map<Integer,Integer> node_a, Map<Integer,Map<Integer,Matrix>> next_state, Map<Integer,Matrix> stateCell, Map<Integer,EventType> event_a, Map<Integer,Integer> class_a, boolean isSimulation, Map<Integer,Double> outprob_a, Map<Integer,Integer> node_p, int local, Map<Integer,EventType> event_p, Map<Integer,Integer> class_p, Map<Integer,Double> outprob_p, Map<Integer,Double> prob_sync_p, Map<Integer,Sync> sync, Map<Integer,Integer> node_a_sf, Map<Integer,Integer> node_p_sf, Map<Integer,Matrix> depRatesSamples, int samples_collected, Map<Integer,Matrix> arvRatesSamples, Matrix csmask, Map<Integer,Double> enabled_rates, Map<Integer,Integer> enabled_sync, SolverSSA solverSSA)
static org.ejml.data.DMatrixRMaj	Solver_ssa.update_paddings_dense(NetworkStruct sn, Map<Integer,Matrix> stateCell, Matrix statelen, org.ejml.data.DMatrixRMaj tranStateD)

Method parameters in jline.solvers.ssa.handlers with type arguments of type Matrix

Modifier and Type	Method	Description
static void	Solver_ssa.save_log_dense(double dt, Map<Integer,Matrix> cur_state, org.ejml.data.DMatrixRMaj tranStateD, int samples_collected, double[] tranSyncData, Map<Integer,Integer> enabled_sync, int firing_ctr, NetworkStruct sn, Map<Integer,Matrix> nir, Map<Integer,Matrix> stateCell, org.ejml.data.DMatrixRMaj SSqD)
static void	Solver_ssa.save_log_dense(double dt, Map<Integer,Matrix> cur_state, org.ejml.data.DMatrixRMaj tranStateD, int samples_collected, double[] tranSyncData, Map<Integer,Integer> enabled_sync, int firing_ctr, NetworkStruct sn, Map<Integer,Matrix> nir, Map<Integer,Matrix> stateCell, org.ejml.data.DMatrixRMaj SSqD, Collector streamingCollector, double curTime)
static SSAValues	Solver_ssa.solver_ssa(NetworkStruct sn_in, EventCache eventCache, Map<StatefulNode,Matrix> init_state, SolverOptions optionsIn, SolverSSA solverSSA)
static org.ejml.data.DMatrixRMaj	Solver_ssa.update_paddings_dense(NetworkStruct sn, Map<Integer,Matrix> stateCell, Matrix statelen, org.ejml.data.DMatrixRMaj tranStateD)

Constructors in jline.solvers.ssa.handlers with parameters of type Matrix

Modifier	Constructor	Description
	SolverSSAResultNRM(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, NetworkStruct sn)
	SolverSSAResultNRMSpace(Matrix pi, Matrix outspace, Matrix depRates, NetworkStruct sn)

Uses of Matrix in jline.streaming

Methods in jline.streaming with parameters of type Matrix

Modifier and Type	Method	Description
void	Collector.recordState(double simulationTime, double dt, Matrix nirState, Matrix depRates, Matrix arvRates)	Record state observation from simulation loop.

Uses of Matrix in jline.util

Fields in jline.util declared as Matrix

Modifier and Type	Field	Description
Matrix	Maths.laplaceApproxReturn.H
Matrix	PopulationLattice.sprodResult.n
Matrix	PopulationLattice.sprodResult.s
Matrix	PopulationLattice.sprodResult.S
final Matrix	UniqueRowResult.sortedMatrix
final Matrix	UniqueRowResult.vi

Methods in jline.util that return Matrix

Modifier and Type	Method	Description
static Matrix	Maths.binHist(Matrix v, int minVal, int maxVal)	Implementation of MATLAB "hist": puts elements of v into k bins
static Matrix	Maths.circul(int c)	Returns a circulant matrix of order c.
static Matrix	Maths.circul(Matrix c)	Returns a circulant matrix from the given first column.
static Matrix	Maths.matrixExp(Matrix matrix)	Adapted from jblas and IHMC Original documentation:
static Matrix	Maths.multichoose(double n, double k)
static Matrix	Maths.multichoose(int n, int k)	Generates all combinations of n objects taken k at a time with repetition (multichoose).
static Matrix	Maths.multiChooseCon(Matrix n, double S)
static Matrix	Maths.nCk(Matrix v, int k)	Computes the combinations of the elements in v taken k at a time
static Matrix	Maths.num_grad_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static Matrix	Maths.num_hess_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static Matrix	Maths.permutations(Matrix vec)
static Matrix	PopulationLattice.pprod(Matrix n)	Initializes a population product iterator.
static Matrix	PopulationLattice.pprod(Matrix n, Matrix N)	Advances to the next population state in lexicographic order.
static Matrix	PopulationLattice.pprodcon(Matrix n, Matrix lb, Matrix ub)
static Matrix	Maths.setdiff(Matrix A, Matrix B)	Set difference operation for Matrix objects that are vectors.
static Matrix	GMMUtils.sgmmConvolve(Matrix sgmm1, Matrix sgmm2)	Convolves two simplified GMMs (sum of independent random variables).
static Matrix	GMMUtils.sgmmMixture(Matrix sgmm1, Matrix sgmm2, double p1, double p2)	Creates a mixture of two simplified GMMs.
static Matrix	Maths.uniqueAndSort(Matrix space)
static Matrix	Maths.uniquePerms(Matrix vec)

Methods in jline.util that return types with arguments of type Matrix

Modifier and Type	Method	Description
static List<Matrix>	Maths.multiChooseCombinations(int k, int n)	Generate all combinations of distributing n items into k bins

Methods in jline.util with parameters of type Matrix

Modifier and Type	Method	Description
void	PrecomputedCDFunction.addValue(Matrix state, double value)	Adds a pre-computed value for a specific state.
Double	PrecomputedCDFunction.apply(Matrix ni)	Applies the function to the given state.
static Matrix	Maths.binHist(Matrix v, int minVal, int maxVal)	Implementation of MATLAB "hist": puts elements of v into k bins
static Matrix	Maths.circul(Matrix c)	Returns a circulant matrix from the given first column.
static int	PopulationLattice.hashpop(Matrix n, Matrix N)	Computes a hash index for a population vector within a lattice.
static int	PopulationLattice.hashpop(Matrix n, Matrix N, int R, Matrix prods)	Computes a hash index for a population vector using precomputed products.
static Maths.laplaceApproxReturn	Maths.laplaceapprox_h(Matrix x0, SerializableFunction<Matrix,Matrix> h)
static Maths.laplaceApproxComplexReturn	Maths.laplaceapprox_h_complex(Matrix x0, SerializableFunction<Matrix,ComplexMatrix> h)
static double	Maths.logmeanexp(Matrix x)
static double	Utils.mape(Matrix approx, Matrix exact)	Return mean absolute percentage error of approx with respect to exact
static Utils.MapeResult	Utils.mapeWithNanMean(Matrix approx, Matrix exact)	Polymorphic version that returns both MAPE and nanMean.
static Matrix	Maths.matrixExp(Matrix matrix)	Adapted from jblas and IHMC Original documentation:
static int	Maths.maxpos(Matrix v)	Returns the position of the maximum value in a vector.
static int[]	Maths.maxpos(Matrix v, int n)	Returns the positions of the n largest values in a vector.
static int	Maths.minpos(Matrix v)	Returns the position of the minimum value in a vector.
static int[]	Maths.minpos(Matrix v, int n)	Returns the positions of the n smallest values in a vector.
static Matrix	Maths.multiChooseCon(Matrix n, double S)
static double	Maths.multinomialln(Matrix n)
static Matrix	Maths.nCk(Matrix v, int k)	Computes the combinations of the elements in v taken k at a time
static Matrix	Maths.num_grad_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static ComplexMatrix	Maths.num_grad_h_complex(Matrix x0, double h, SerializableFunction<Matrix,ComplexMatrix> hfun)
static Matrix	Maths.num_hess_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static ComplexMatrix	Maths.num_hess_h_complex(Matrix x0, double h, SerializableFunction<Matrix,ComplexMatrix> hfun)
static Matrix	Maths.permutations(Matrix vec)
static Matrix	PopulationLattice.pprod(Matrix n)	Initializes a population product iterator.
static Matrix	PopulationLattice.pprod(Matrix n, Matrix N)	Advances to the next population state in lexicographic order.
static Matrix	PopulationLattice.pprodcon(Matrix n, Matrix lb, Matrix ub)
static int	Maths.probchoose(Matrix p)	Choose an element index according to probability vector.
static org.apache.commons.math3.complex.Complex[]	Maths.roots(Matrix coefficients)
static void	MatFileUtils.saveCTMCWorkspace(Matrix stateSpace, Matrix infGen, Matrix pi, String filename)	Saves CTMC solver workspace to a .mat file
static void	MatFileUtils.saveMatrix(Matrix matrix, String variableName, String filename)	Saves a single matrix to a .mat file
static Matrix	Maths.setdiff(Matrix A, Matrix B)	Set difference operation for Matrix objects that are vectors.
static Matrix	GMMUtils.sgmmConvolve(Matrix sgmm1, Matrix sgmm2)	Convolves two simplified GMMs (sum of independent random variables).
static double	GMMUtils.sgmmE1(Matrix sgmm)	Calculates the first moment (E[X]) of a simplified GMM.
static double	GMMUtils.sgmmE2(Matrix sgmm)	Calculates the second moment (E[X²]) of a simplified GMM.
static double	GMMUtils.sgmmMean(Matrix sgmm)	Calculates the mean of a simplified GMM directly from matrix representation.
static Matrix	GMMUtils.sgmmMixture(Matrix sgmm1, Matrix sgmm2, double p1, double p2)	Creates a mixture of two simplified GMMs.
static double[]	GMMUtils.sgmmRand(Matrix sgmm, int n)	Generates random samples from a simplified GMM representation.
static double	GMMUtils.sgmmStd(Matrix sgmm)	Calculates the standard deviation of a simplified GMM.
static double	GMMUtils.sgmmVar(Matrix sgmm)	Calculates the variance of a simplified GMM.
static double	Maths.simplex_fun(double[] x, Matrix L, Matrix N)	Computes a specialized function used in simplex-based optimization algorithms.
static PopulationLattice.sprodResult	PopulationLattice.sprod(int M, Matrix N)
static PopulationLattice.sprodResult	PopulationLattice.sprod(Matrix s, Matrix S, MatrixCell D)
static List<Integer>	Maths.sub2ind(Matrix dims, Matrix row, Matrix col)
static Matrix	Maths.uniqueAndSort(Matrix space)
static Matrix	Maths.uniquePerms(Matrix vec)

Method parameters in jline.util with type arguments of type Matrix

Modifier and Type	Method	Description
static Maths.laplaceApproxReturn	Maths.laplaceapprox_h(Matrix x0, SerializableFunction<Matrix,Matrix> h)
static Maths.laplaceApproxReturn	Maths.laplaceapprox_h(Matrix x0, SerializableFunction<Matrix,Matrix> h)
static Maths.laplaceApproxComplexReturn	Maths.laplaceapprox_h_complex(Matrix x0, SerializableFunction<Matrix,ComplexMatrix> h)
static Matrix	Maths.num_grad_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static Matrix	Maths.num_grad_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static ComplexMatrix	Maths.num_grad_h_complex(Matrix x0, double h, SerializableFunction<Matrix,ComplexMatrix> hfun)
static Matrix	Maths.num_hess_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static Matrix	Maths.num_hess_h(Matrix x0, double h, SerializableFunction<Matrix,Matrix> hfun)
static ComplexMatrix	Maths.num_hess_h_complex(Matrix x0, double h, SerializableFunction<Matrix,ComplexMatrix> hfun)
static void	MatFileUtils.saveWorkspace(Map<String,Matrix> matrices, String filename)	Saves multiple matrices to a .mat file as a workspace

Constructors in jline.util with parameters of type Matrix

Modifier	Constructor	Description
	laplaceApproxReturn(Matrix H, double I, double logI)
	sprodResult(Matrix s, Matrix n, Matrix S, MatrixCell D)
	UniqueRowResult(Matrix sortedMatrix, Matrix vi, Map<Integer,List<Integer>> vj)

Uses of Matrix in jline.util.graph

Methods in jline.util.graph that return Matrix

Modifier and Type	Method	Description
static Matrix	DirectedGraph.kahn(Matrix adj)	Performs topological sorting using Kahn's algorithm.
Matrix	DirectedGraph.toMatrix()
Matrix	UndirectedGraph.toMatrix()

Methods in jline.util.graph with parameters of type Matrix

Modifier and Type	Method	Description
static boolean	DirectedGraph.isDAG(Matrix adj)	Tests if the given adjacency matrix represents a Directed Acyclic Graph (DAG).
static Matrix	DirectedGraph.kahn(Matrix adj)	Performs topological sorting using Kahn's algorithm.

Constructors in jline.util.graph with parameters of type Matrix

Modifier	Constructor	Description
	DirectedGraph(Matrix param)	Constructs a directed graph with the given adjacency matrix (no column filtering).
	DirectedGraph(Matrix param, Set<Integer> colsToIgnore)	Constructs a directed graph with the given adjacency matrix and column filter.
	UndirectedGraph(Matrix param)
	UndirectedGraph(Matrix param, Set<Integer> colsToIgnore)	Constructs an undirected graph with the given adjacency matrix and column filter.
	UndirectedGraph(Matrix param, Set<Integer> colsToIgnore, boolean normalize)	Constructs an undirected graph with optional weight normalization.

Uses of Matrix in jline.util.matrix

Fields in jline.util.matrix declared as Matrix

Modifier and Type	Field	Description
Matrix	ComplexMatrix.im	The imaginary component of the complex matrix
Matrix	ComplexMatrix.real	The real component of the complex matrix

Methods in jline.util.matrix that return Matrix

Modifier and Type	Method	Description
Matrix	Matrix.add(double alpha)	Adds a scalar multiple of the all-ones matrix to this matrix: this + alpha * 1.
Matrix	Matrix.add(double alpha, Matrix matrix)	Adds alpha * matrix to this matrix.
Matrix	Matrix.add(Matrix matrix)	Adds another matrix to this matrix: this + matrix.
static Matrix	Matrix.allbut(Matrix y, int k)	Returns all elements in a matrix except the first ones
static Matrix	Matrix.broadcastColPlusRow(Matrix colVector, Matrix rowVector)	Computes the element-wise sum of a column vector and a row vector, producing a matrix where each entry (i, j) is the sum of colVector[i] and rowVector[j].
static Matrix	Matrix.cartesian(Matrix matrixA, Matrix matrixB)	Cartesian product of two matrices.
Matrix	Matrix.ceil()	Returns a new matrix where each element is the ceiling of the corresponding element in this matrix.
Matrix	Matrix.ceilEq()	Applies the ceiling operation in-place to each element of this matrix.
static Matrix	Matrix.cell2mat(Map<Integer,Matrix> cellArray)	Concatenates a collection of matrices stored in a map into a single row vector.
static Matrix	Matrix.cellsum(Map<Integer,Matrix> cellArray)	Computes the element-wise sum of all matrices stored in a map.
Matrix	MatrixCell.cellsum()	Computes the element-wise sum of all matrices in this cell.
Matrix	Matrix.colon()	Returns the matrix in column-major order.
Matrix	Matrix.columnMajorOrder()	Equivalent to the colon operator in MATLAB (:).
Matrix	Matrix.compatibleSizesAdd(Matrix b)	Performs element-wise addition with shape broadcasting where applicable.
Matrix	Matrix.concatCols(Matrix other)	Concatenates this matrix with another matrix horizontally.
static Matrix	Matrix.concatColumns(Matrix left, Matrix right, Matrix out)	Concatenates two matrices horizontally (column-wise).
static Matrix	Matrix.concatRows(Matrix top, Matrix bottom, Matrix out)	Concatenates two matrices vertically (row-wise).
Matrix	Matrix.copy()	Returns a deep copy of this matrix.
Matrix	Matrix.countEachRow(double val)	Counts the number of occurrences of a value in each row of the matrix.
Matrix	Matrix.createBlockDiagonal(Matrix matrix2)	Creates a block diagonal matrix by placing the current matrix in the top-left and another matrix (if provided) in the bottom-right.
static Matrix	Matrix.createLike(Matrix B)	Creates a new empty matrix with the same shape and internal structure as the given matrix.
Matrix	Matrix.cumsumViaCol()	Computes the cumulative sum of the matrix down each column.
Matrix	Matrix.cumsumViaRow()	Computes the cumulative sum of the matrix across each row.
static Matrix	Matrix.decorate(Matrix inspace1, Matrix inspace2)
static Matrix	Matrix.diag(double... values)	Creates a square diagonal matrix from the given values.
static Matrix	Matrix.diagMatrix(double[] values)	Creates a square diagonal matrix from a given array of values.
static Matrix	Matrix.diagMatrix(Matrix values)	Creates a square diagonal matrix from the elements of a column or row vector matrix.
static Matrix	Matrix.diagMatrix(Matrix A, double[] values, int offset, int length)	Creates or fills a square diagonal matrix with the specified values.
Matrix	Matrix.div(Matrix den)	Performs element-wise division between this matrix and the provided matrix.
static Matrix	Matrix.dlyap(Matrix A, Matrix B, Matrix C)	Solves the discrete Sylvester equation A * X * B - X + C = 0.
Matrix	Matrix.elementDiv(Matrix B)	Performs element-wise division of this matrix by another matrix.
Matrix	Matrix.elementDivide(Matrix b)	Performs element-wise division with another matrix.
Matrix	Matrix.elementIncrease(double val)	Increases each element of the matrix by a constant value.
Matrix	Matrix.elementMult(Matrix B)	Performs in-place element-wise multiplication with another matrix.
Matrix	Matrix.elementMult(Matrix B, Matrix output)	Performs element-wise multiplication with another matrix, storing the result in the given output matrix.
Matrix	Matrix.elementMultWithVector(Matrix B)	Performs element-wise multiplication between this matrix and a row vector.
Matrix	Matrix.elementPow(double a)	Raises each non-zero element of the matrix to the specified power.
Matrix	Matrix.elementPower(double t)	Raises each element of the matrix to the given power.
Matrix	Matrix.exp()	Applies the exponential function to each element of the matrix.
Matrix	Matrix.expm()	Computes the matrix exponential.
Matrix	Matrix.expm_higham()	Computes the matrix exponential using Higham's scaling and squaring method.
static Matrix	Matrix.extract(Matrix src, int srcX0, int srcX1, int srcY0, int srcY1)	Extracts a rectangular submatrix from the given source matrix.
Matrix	Matrix.extractCols(int col0, int col1)	Extracts a range of columns from this matrix (instance method).
static Matrix	Matrix.extractColumn(Matrix A, int column, Matrix out)	Extracts a single column from the given matrix.
static Matrix	Matrix.extractColumns(Matrix A, int col0, int col1)	Extracts a range of columns from the matrix [col0:col1).
static Matrix	Matrix.extractColumns(Matrix A, int col0, int col1, Matrix out)	Extracts a range of columns from the matrix [col0:col1) into a destination matrix.
Matrix	Matrix.extractRows(int row0, int row1)	Extracts rows from this matrix (instance method).
static Matrix	Matrix.extractRows(Matrix A, int row0, int row1)	Extracts a range of rows from the matrix [row0:row1).
static Matrix	Matrix.extractRows(Matrix A, int row0, int row1, Matrix out)	Extracts a range of rows from the matrix [row0:row1) into a destination matrix.
static Matrix	Matrix.eye(int length)	Creates an identity matrix of given size.
Matrix	Matrix.fact()	Computes the factorial of each element in the matrix.
Matrix	Matrix.factln()	Computes the natural logarithm of the factorial for each element.
static Matrix	Matrix.factln(Matrix n)	Computes the natural logarithm of the factorial (log(x!)) for each element in the input matrix.
Matrix	Matrix.fill(double val)	Fills all entries in the matrix with the given value.
Matrix	Matrix.find()	Returns the linear indices of all non-zero elements in the matrix.
Matrix	Matrix.findNonNegative()	Returns the linear indices of all elements that are non-negative (≥ 0).
Matrix	Matrix.findNumber(double number)	Finds all linear indices where the matrix has a specific value.
Matrix	Matrix.findZero()	Finds all linear indices where the matrix value is zero.
Matrix	Matrix.fromArray2D(double[][] matrix)	Populates the matrix from a 2D double array.
Matrix	Matrix.fromArray2D(int[][] matrix)	Populates the matrix from a 2D integer array.
static Matrix	Matrix.fromRows(List<List<Double>> rows)	Constructs a Matrix from a list of rows, where each inner list is a row.
Matrix	MatrixCell.get(int i)	Retrieves the matrix stored at the specified index.
Matrix	Matrix.getColumn(int j)	Returns a column of the matrix as a new single-column matrix.
Matrix	Matrix.getRow(int i)	Returns the specified row as a single-row matrix.
Matrix	Matrix.getRowsFrom(int row)	Returns a new matrix consisting of rows from the given start index to the end.
Matrix	Matrix.getSlice(boolean[] rowFlags, boolean[] colFlags)	Extracts a submatrix from rows/columns marked as true in input flags.
Matrix	Matrix.getSlice(int r0, int r1, int c0, int c1)	Extracts a submatrix based on row/column bounds.
static Matrix	Matrix.getSubMatrix(Matrix sourceMatrix, int x0, int x1, int y0, int y1)	Extracts a submatrix from the source matrix using zero-based index ranges.
Matrix	Matrix.getSubMatrix(Matrix rows, Matrix cols)	Returns a matrix consisting of rows and columns selected by two index matrices.
Matrix	Matrix.hadamard(Matrix B)	Performs the Hadamard (element-wise) product of two matrices.
Matrix	Matrix.inv()	Computes the inverse of the matrix.
static Matrix	Matrix.inv(Matrix m)	Computes the inverse of the given matrix.
Matrix	Matrix.kron(Matrix b)	Computes the Kronecker product of this matrix and another matrix.
Matrix	Matrix.krons(Matrix other)	Computes the Kronecker sum of two matrices: A ⊕ B = A \otimes I + I \otimes B, where \otimes is the Kronecker product and I is the identity matrix of matching size.
Matrix	Matrix.leftMatrixDivide(Matrix b)	Solves the equation AX = B for X, where A is this matrix and B is the right-hand side.
Matrix	Matrix.log()	Applies the natural logarithm element-wise.
Matrix	MatrixEquation.lookupSimple(String token)	Retrieves a matrix result from the equation context by variable name.
static Matrix	Matrix.lyap(Matrix A, Matrix B, Matrix C, Matrix D)	Computes the solution to the continuous-time Lyapunov equation AX + XAᵀ + Q = 0.
static Matrix	Matrix.matrixAddVector(Matrix matrix, Matrix vector)	Adds a vector to each row or column of the matrix, depending on the vector's orientation.
Matrix	Matrix.meanCol()	Computes the mean of each column.
Matrix	Matrix.meanRow()	Computes the mean of each row.
Matrix	Matrix.mult(Matrix B)	Performs matrix multiplication: this * B
Matrix	Matrix.mult(Matrix B, Matrix out)	Performs matrix multiplication: this * B
Matrix	Matrix.neg()	Returns the negation of this matrix (all elements multiplied by -1).
static Matrix	Matrix.negative(Matrix a)	Negates all elements in the matrix and returns the result.
static Matrix	Matrix.oneMinusMatrix(Matrix matrix)	Computes the matrix 1 - A, where diagonal entries become 1 - A(i, i) and off-diagonal entries become -A(i, j).
static Matrix	Matrix.oner(Matrix N, Integer s)	Decreases a single element of an integer vector by one.
static Matrix	Matrix.oner(Matrix N, List<Integer> r)	Decreases multiple elements of an integer vector by one.
static Matrix	Matrix.ones(int rows, int cols)	Creates a matrix of the given shape filled with ones.
Matrix	Matrix.pinv()	Computes the Moore-Penrose pseudo-inverse of the matrix using SVD.
static Matrix	Matrix.pow(Matrix a, int b)	Computes the matrix power A^b for a non-negative integer exponent b.
static Matrix	Matrix.readFromFile(String fileName)	Reads a CSV-formatted matrix from a file.
Matrix	Matrix.reciprocal()	Computes the element-wise reciprocal (1/x) of the matrix.
Matrix	Matrix.repmat(int rows, int cols)	Repeats the matrix to match the specified row and column replication.
Matrix	Matrix.reverse()	Reverses the elements of a vector (row or column) matrix.
Matrix	Matrix.reverseRows()	Reverses the order of rows in the matrix.
Matrix	Matrix.rightMatrixDivide(Matrix b)	Performs right matrix division A / B = A * inv(B)
static Matrix	Matrix.robustLeftDivide(Matrix A, Matrix B)	Robust linear solve for A·X = B that handles singular matrices.
Matrix	Matrix.safeMult(Matrix B)
Matrix	Matrix.scale(double scalar)	Scales the matrix by the given scalar value.
static Matrix	Matrix.scaleMult(Matrix a, double n)	Multiplies all elements of a matrix by a scalar.
Matrix	MatrixCell.set(int i, Matrix D)	Stores a matrix at the specified index.
Matrix	Matrix.setColumn(int j, Matrix col)	Sets the specified column to the values in the given vector.
Matrix	Matrix.setColumns(int j0, int j1, Matrix cols)	Sets multiple columns starting from column index j0 to j1 (exclusive) using values from another matrix.
Matrix	Matrix.setRow(int j, Matrix row)	Sets the specified row to the values in the given vector.
Matrix	Matrix.setRows(int i0, int i1, Matrix rows)	Sets multiple rows starting from row index i0 to i1 (exclusive) using values from another matrix.
Matrix	Matrix.setSlice(int rowStart, int rowEnd, int colStart, int colEnd, Matrix newSlice)	Returns a new matrix representing the updated slice after assigning values from newSlice.
static Matrix	Matrix.singleton(double value)	Creates a 1×1 matrix containing a single scalar value.
Matrix	Matrix.sort()	Returns a new matrix with the non-zero values sorted in ascending order.
Matrix	Matrix.sortEq()	Sorts the current matrix's non-zero values in place.
Matrix	Matrix.sqrt()	Computes the element-wise square root of the matrix.
Matrix	Matrix.square()	Computes the matrix multiplied by itself.
Matrix	Matrix.sub(double x)	Subtract a scalar from all elements.
Matrix	Matrix.sub(double alpha, Matrix matrix)	Subtracts alpha-scaled version of the provided matrix.
Matrix	Matrix.sub(Matrix matrix)	Subtracts another matrix.
Matrix	Matrix.sumCols()	Sums the values in each column and returns the results as a row vector.
Matrix	Matrix.sumCols(int startRow, int endRow)	Computes the sum of a subset of rows for each column.
Matrix	Matrix.sumRows()	Computes the sum of each row and returns the result as a column vector.
Matrix	Matrix.sumRows(int startCol, int endCol)	Computes the sum over a subrange of columns for each row.
static Matrix	Matrix.sylv(Matrix A, Matrix B, Matrix C)	Solves the Sylvester equation A·X + X·B = -C using a Schur decomposition-based method.
Matrix	Matrix.transpose()	Computes the transpose of the current matrix.
static Matrix	Matrix.tril(Matrix matrix)	Returns the lower triangular part of a matrix (zeroing elements above the main diagonal).
static Matrix	Matrix.tril(Matrix matrix, int k)	Returns the elements on and below the kth diagonal of matrix A.
static Matrix	Matrix.union(Matrix A, Matrix B)	Computes the union of two matrices A and B.
Matrix	Matrix.uniqueInCol(int colIdx)	Finds unique integer values in the specified column of the matrix.
Matrix	Matrix.uniqueInRow(int rowIdx)	Finds unique integer values in the specified row of the matrix.
Matrix	Matrix.uniqueNonNegativeInCol(int colIdx)	Finds unique positive values (strictly greater than 0) in the specified column.
Matrix	Matrix.uniqueNonNegativeInRow(int rowIdx)	Finds unique positive values (strictly greater than 0) in the specified row.
Matrix	Matrix.uniqueNonZerosInCol(int colIdx)	Finds unique non-zero values in the specified column.
Matrix	Matrix.uniqueNonZerosInRow(int rowIdx)	Finds unique non-zero values in the specified row.
static Matrix	Matrix.zeros(int rows, int cols)	Creates a matrix of the specified shape filled with zeros.

Methods in jline.util.matrix that return types with arguments of type Matrix

Modifier and Type	Method	Description
Map<String,Matrix>	Matrix.qr()	Performs QR decomposition on the matrix.
Map<String,Matrix>	Matrix.schur()	Computes the Schur decomposition with the default method and iteration count.
Map<String,Matrix>	Matrix.schur(String method, Integer iter)	Computes the Schur decomposition of the matrix.
Map<Integer,Matrix>	MatrixCell.toMap()	Creates a copy of the internal mapping from indices to matrices.

Methods in jline.util.matrix with parameters of type Matrix

Modifier and Type	Method	Description
Matrix	Matrix.add(double alpha, Matrix matrix)	Adds alpha * matrix to this matrix.
Matrix	Matrix.add(Matrix matrix)	Adds another matrix to this matrix: this + matrix.
void	Matrix.addEq(double alpha, Matrix matrix)	Adds alpha * matrix to this matrix in-place: this += alpha * matrix.
void	Matrix.addEq(Matrix matrix)	Adds another matrix to this matrix in-place: this += matrix.
static Matrix	Matrix.allbut(Matrix y, int k)	Returns all elements in a matrix except the first ones
static Matrix	Matrix.broadcastColPlusRow(Matrix colVector, Matrix rowVector)	Computes the element-wise sum of a column vector and a row vector, producing a matrix where each entry (i, j) is the sum of colVector[i] and rowVector[j].
static Matrix	Matrix.cartesian(Matrix matrixA, Matrix matrixB)	Cartesian product of two matrices.
static double[]	Matrix.columnMatrixToDoubleArray(Matrix columnMatrix)	Converts a column matrix (of size m x 1) to a dense double array of length m.
static boolean	Matrix.compare(Matrix A, Matrix B, String op)	Compares two matrices element-wise using a specified comparison operator.
boolean	Matrix.compareMatrix(Matrix matrix)	Compares this matrix to another matrix for approximate equality.
Matrix	Matrix.compatibleSizesAdd(Matrix b)	Performs element-wise addition with shape broadcasting where applicable.
Matrix	Matrix.concatCols(Matrix other)	Concatenates this matrix with another matrix horizontally.
static Matrix	Matrix.concatColumns(Matrix left, Matrix right, Matrix out)	Concatenates two matrices horizontally (column-wise).
static Matrix	Matrix.concatRows(Matrix top, Matrix bottom, Matrix out)	Concatenates two matrices vertically (row-wise).
Matrix	Matrix.createBlockDiagonal(Matrix matrix2)	Creates a block diagonal matrix by placing the current matrix in the top-left and another matrix (if provided) in the bottom-right.
static Matrix	Matrix.createLike(Matrix B)	Creates a new empty matrix with the same shape and internal structure as the given matrix.
static Matrix	Matrix.decorate(Matrix inspace1, Matrix inspace2)
static Matrix	Matrix.diagMatrix(Matrix values)	Creates a square diagonal matrix from the elements of a column or row vector matrix.
static Matrix	Matrix.diagMatrix(Matrix A, double[] values, int offset, int length)	Creates or fills a square diagonal matrix with the specified values.
Matrix	Matrix.div(Matrix den)	Performs element-wise division between this matrix and the provided matrix.
void	Matrix.divEq(Matrix den)	Performs in-place element-wise division between this matrix and the provided matrix.
void	Matrix.divide(double scalar, Matrix outputB, boolean flag)	Divides this matrix by a scalar and stores the result in the output matrix.
static Matrix	Matrix.dlyap(Matrix A, Matrix B, Matrix C)	Solves the discrete Sylvester equation A * X * B - X + C = 0.
double	RowView.dotProduct(Matrix columnVector)	Computes the dot product of this row with a column vector.
Matrix	Matrix.elementDiv(Matrix B)	Performs element-wise division of this matrix by another matrix.
Matrix	Matrix.elementDivide(Matrix b)	Performs element-wise division with another matrix.
static double	Matrix.elementMinNonZero(Matrix matrix)	Returns the smallest non-zero positive element in the given matrix.
Matrix	Matrix.elementMult(Matrix B)	Performs in-place element-wise multiplication with another matrix.
Matrix	Matrix.elementMult(Matrix B, Matrix output)	Performs element-wise multiplication with another matrix, storing the result in the given output matrix.
Matrix	Matrix.elementMultWithVector(Matrix B)	Performs element-wise multiplication between this matrix and a row vector.
static Matrix	Matrix.extract(Matrix src, int srcX0, int srcX1, int srcY0, int srcY1)	Extracts a rectangular submatrix from the given source matrix.
static void	Matrix.extract(Matrix src, int srcX0, int srcX1, int srcY0, int srcY1, Matrix dst, int dstY0, int dstX0)	Extracts a rectangular submatrix from a source matrix and stores it in a destination matrix.
static Matrix	Matrix.extractColumn(Matrix A, int column, Matrix out)	Extracts a single column from the given matrix.
static Matrix	Matrix.extractColumns(Matrix A, int col0, int col1)	Extracts a range of columns from the matrix [col0:col1).
static Matrix	Matrix.extractColumns(Matrix A, int col0, int col1, Matrix out)	Extracts a range of columns from the matrix [col0:col1) into a destination matrix.
static void	Matrix.extractDiag(Matrix A, Matrix outputB)	Extracts the diagonal elements of a matrix and stores them in a destination matrix.
static Matrix	Matrix.extractRows(Matrix A, int row0, int row1)	Extracts a range of rows from the matrix [row0:row1).
static Matrix	Matrix.extractRows(Matrix A, int row0, int row1, Matrix out)	Extracts a range of rows from the matrix [row0:row1) into a destination matrix.
static Matrix	Matrix.factln(Matrix n)	Computes the natural logarithm of the factorial (log(x!)) for each element in the input matrix.
static List<Integer>	Matrix.findIndexWithZeroSum(Matrix matrix, boolean isRow)	Finds the indices of all rows or columns in a matrix that have a sum of zero.
static List<Integer>	Matrix.findRows(Matrix matrix, Matrix row)	Finds the indices of all rows in a matrix that exactly match a given row vector.
static double	Matrix.firstNorm(Matrix a)	Computes the 1-norm (maximum absolute column sum) of the matrix.
static Matrix	Matrix.getSubMatrix(Matrix sourceMatrix, int x0, int x1, int y0, int y1)	Extracts a submatrix from the source matrix using zero-based index ranges.
Matrix	Matrix.getSubMatrix(Matrix rows, Matrix cols)	Returns a matrix consisting of rows and columns selected by two index matrices.
Matrix	Matrix.hadamard(Matrix B)	Performs the Hadamard (element-wise) product of two matrices.
static double	Matrix.infNorm(Matrix a)	Computes the infinity norm (maximum absolute row sum) of the matrix.
void	Matrix.insertSubMatrix(int start_row, int start_col, int end_row, int end_col, Matrix matrix_to_be_inserted)	Inserts a sub-matrix into the current matrix at the specified location.
static List<Double>	Matrix.intersect(Matrix matrixA, Matrix matrixB)	Computes the intersection of scalar values present in two matrices.
static Matrix	Matrix.inv(Matrix m)	Computes the inverse of the given matrix.
boolean	Matrix.isEqualTo(Matrix m)	Checks if two matrices are exactly equal.
boolean	Matrix.isEqualToTol(Matrix m, double tol)	Checks if two matrices are equal within a specified tolerance.
Matrix	Matrix.kron(Matrix b)	Computes the Kronecker product of this matrix and another matrix.
Matrix	Matrix.krons(Matrix other)	Computes the Kronecker sum of two matrices: A ⊕ B = A \otimes I + I \otimes B, where \otimes is the Kronecker product and I is the identity matrix of matching size.
Matrix	Matrix.leftMatrixDivide(Matrix b)	Solves the equation AX = B for X, where A is this matrix and B is the right-hand side.
static double	Matrix.logSum(Matrix matrix)	Computes the sum of the natural logarithms of all elements in the matrix.
static double	Matrix.logsumexp(Matrix x)	Computes log(sum_i exp(x_i)) in a numerically stable way (log-sum-exp trick).
static Matrix	Matrix.lyap(Matrix A, Matrix B, Matrix C, Matrix D)	Computes the solution to the continuous-time Lyapunov equation AX + XAᵀ + Q = 0.
static int	Matrix.matchrow(Matrix matrix, Matrix row)	Returns the index of the row in the matrix that exactly matches the given row vector.
static Matrix	Matrix.matrixAddVector(Matrix matrix, Matrix vector)	Adds a vector to each row or column of the matrix, depending on the vector's orientation.
static double	Matrix.maxAbsDiff(Matrix a, Matrix b)	Computes the maximum relative absolute difference between corresponding elements of two matrices: max(abs((a - b) / b)).
Matrix	Matrix.mult(Matrix B)	Performs matrix multiplication: this * B
Matrix	Matrix.mult(Matrix B, Matrix out)	Performs matrix multiplication: this * B
void	Matrix.multEq(Matrix B)	Replaces this matrix with the result of this * B.
static Matrix	Matrix.negative(Matrix a)	Negates all elements in the matrix and returns the result.
static Matrix	Matrix.oneMinusMatrix(Matrix matrix)	Computes the matrix 1 - A, where diagonal entries become 1 - A(i, i) and off-diagonal entries become -A(i, j).
static Matrix	Matrix.oner(Matrix N, Integer s)	Decreases a single element of an integer vector by one.
static Matrix	Matrix.oner(Matrix N, List<Integer> r)	Decreases multiple elements of an integer vector by one.
static Matrix	Matrix.pow(Matrix a, int b)	Computes the matrix power A^b for a non-negative integer exponent b.
static double[][][]	Matrix.removeRows(double[][][] array, Matrix rowsToRemove)
Matrix	Matrix.rightMatrixDivide(Matrix b)	Performs right matrix division A / B = A * inv(B)
static Matrix	Matrix.robustLeftDivide(Matrix A, Matrix B)	Robust linear solve for A·X = B that handles singular matrices.
Matrix	Matrix.safeMult(Matrix B)
void	Matrix.scaleEq(double scalar, Matrix output)	Scales this matrix by the given scalar value and stores the result in the provided output matrix.
static Matrix	Matrix.scaleMult(Matrix a, double n)	Multiplies all elements of a matrix by a scalar.
Matrix	MatrixCell.set(int i, Matrix D)	Stores a matrix at the specified index.
Matrix	Matrix.setColumn(int j, Matrix col)	Sets the specified column to the values in the given vector.
Matrix	Matrix.setColumns(int j0, int j1, Matrix cols)	Sets multiple columns starting from column index j0 to j1 (exclusive) using values from another matrix.
Matrix	Matrix.setRow(int j, Matrix row)	Sets the specified row to the values in the given vector.
Matrix	Matrix.setRows(int i0, int i1, Matrix rows)	Sets multiple rows starting from row index i0 to i1 (exclusive) using values from another matrix.
Matrix	Matrix.setSlice(int rowStart, int rowEnd, int colStart, int colEnd, Matrix newSlice)	Returns a new matrix representing the updated slice after assigning values from newSlice.
void	Matrix.setSliceEq(int rowStart, int rowEnd, int colStart, int colEnd, Matrix newSlice)	Sets the values of a submatrix (in-place) using the specified newSlice matrix.
void	Matrix.setTo(Matrix m)	Copies the data from another matrix into this matrix.
static boolean	Matrix.solve(Matrix a, Matrix b, Matrix x)	Solves the sparse linear system Ax = b.
static boolean	Matrix.solveDirect(Matrix a, Matrix b, Matrix x)	Solves the linear system A*x = b directly using LU decomposition without singularity checks.
static boolean	Matrix.solveSafe(Matrix a, Matrix b, Matrix x)	Solves the linear system Ax = b for x, handling singular matrices gracefully.
static Ret.SpectralDecomposition	Matrix.spectd(Matrix A)	Computes the spectral decomposition of a matrix A using its eigendecomposition.
Matrix	Matrix.sub(double alpha, Matrix matrix)	Subtracts alpha-scaled version of the provided matrix.
Matrix	Matrix.sub(Matrix matrix)	Subtracts another matrix.
void	Matrix.subEq(double alpha, Matrix matrix)	Subtracts a scaled matrix from the current matrix in place.
void	Matrix.subEq(Matrix matrix)	Subtracts a matrix from the current matrix in place.
static double	Matrix.sumCumprod(Matrix matrix)	Computes the sum of the cumulative product along a row vector.
static Matrix	Matrix.sylv(Matrix A, Matrix B, Matrix C)	Solves the Sylvester equation A·X + X·B = -C using a Schur decomposition-based method.
org.ejml.data.DMatrixSparseCSC	Matrix.toDMatrixSparseCSC(Matrix matrix)	Converts a specified matrix to a copy of its underlying DMatrixSparseCSC structure.
static Matrix	Matrix.tril(Matrix matrix)	Returns the lower triangular part of a matrix (zeroing elements above the main diagonal).
static Matrix	Matrix.tril(Matrix matrix, int k)	Returns the elements on and below the kth diagonal of matrix A.
static Matrix	Matrix.union(Matrix A, Matrix B)	Computes the union of two matrices A and B.
static UniqueRowResult	Matrix.uniqueRowIndexes(Matrix m)	Finds the indices of unique rows in a matrix without returning a matrix of the unique rows themselves.
static UniqueRowResult	Matrix.uniqueRowIndexesFromColumn(Matrix m, int startCol)	Identifies unique rows in a matrix starting from a specified column index.
static UniqueRowResult	Matrix.uniqueRows(Matrix m)	Finds all unique rows in a matrix and returns the unique sorted rows, along with mapping indices to/from the original matrix.
static Set<Set<Integer>>	Matrix.weaklyConnect(Matrix param, Set<Integer> colsToIgnore)	Weakly-connected components of a sub-matrix.

Method parameters in jline.util.matrix with type arguments of type Matrix

Modifier and Type	Method	Description
static Matrix	Matrix.cell2mat(Map<Integer,Matrix> cellArray)	Concatenates a collection of matrices stored in a map into a single row vector.
static Matrix	Matrix.cellsum(Map<Integer,Matrix> cellArray)	Computes the element-wise sum of all matrices stored in a map.
static int	Matrix.getColIndexSum(Map<Integer,Matrix> cellArray)	Computes the total number of elements across all matrices in a map, summing numRows * numCols for each matrix.

Constructors in jline.util.matrix with parameters of type Matrix

Modifier	Constructor	Description
	ComplexMatrix(Matrix real)	Creates a complex matrix from a real matrix with zero imaginary component.
	ComplexMatrix(Matrix real, Matrix im)	Creates a complex matrix from separate real and imaginary component matrices.
	Matrix(Matrix matrix)	Creates a copy of the specified matrix.
	MatrixCell(Matrix[] x)	Creates a MatrixCell from an array of matrices.
	MatrixCell(Matrix D0, Matrix D1)	Creates a MatrixCell containing exactly two matrices.