Uses of Class
jline.util.MatrixCell

Packages that use MatrixCell

Package	Description
jline.api	Procedural algorithms for solving stochastic models
jline.io	Input/output from the command line or XML files.
jline.lang	Abstractions to declare basic elements of a model.
jline.lang.processes	This package contains statistical distributions used to specify arrival rates, service rates, and item popularities
jline.lib.thirdparty	Classes that partially migrate third-party libraries to Java
jline.solvers.mam	Analysis approaches based on matrix-analytic methods
jline.util	This package contains some fundamental data structures and utilities

Uses of MatrixCell in jline.api

Methods in jline.api that return MatrixCell

Modifier and Type	Method	Description
static MatrixCell	MAM.aph_fit(double e1, double e2, double e3)	Fits an acyclic phase-type (APH) distribution to the given moments of a random variable.
static MatrixCell	MAM.aph_fit(double e1, double e2, double e3, int nmax)	Fits an acyclic phase-type (APH) distribution to the given moments of a random variable.
static MatrixCell	MAM.aph2_assemble(double l1, double l2, double p1)	Assembles an acyclic phase-type (APH) distribution with two phases (APH(2)) using the given parameters.
static MatrixCell	MAM.mamap2m_fit_gamma_fb_mmap(MatrixCell mmap)
static MatrixCell	MAM.map_erlang(double mean, int k)	Fits an Erlang-k process as a Markovian Arrival Process (MAP).
static MatrixCell	MAM.map_exponential(double mean)	Creates a Markovian Arrival Process (MAP) with an exponential inter-arrival time distribution.
static MatrixCell	MAM.map_hyperexp(double mean, double scv, double p)	Fit a two-phase Hyper-exponential renewal process as a MAP
static MatrixCell	MAM.map_mark(MatrixCell MAP, Matrix prob)	Creates a Marked Markovian Arrival Process (MMAP) by marking a given Markovian Arrival Process (MAP) with additional phases based on specified marking probabilities.
static MatrixCell	MAM.map_normalize(MatrixCell MAP)	Sanitizes the (D0, D1) matrices of a Markovian Arrival Process (MAP) stored in a MatrixCell.
static MatrixCell	MAM.map_normalize(Matrix D0, Matrix D1)	Sanitizes the (D0, D1) matrices of a Markovian Arrival Process (MAP) by ensuring all elements are non-negative and adjusting diagonal elements.
MatrixCell	MAM.map_rand()	Generates a random Markovian Arrival Process (MAP) with 2 states.
static MatrixCell	MAM.map_rand(int K)	Generates a random Markovian Arrival Process (MAP) with K states.
MatrixCell	MAM.map_randn()	Generates a random Markovian Arrival Process (MAP) with 2 states using normal distribution with mean 1 and standard deviation 2.
static MatrixCell	MAM.map_randn(int K, double mu, double sigma)	Generates a random Markovian Arrival Process (MAP) with K states using normal distribution.
static MatrixCell	MAM.map_scale(MatrixCell MAP, double newMean)	Rescales the mean inter-arrival time of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static MatrixCell	MAM.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 MatrixCell	MAM.map_sum(MatrixCell MAP, int n)	Computes the Markovian Arrival Process (MAP) representing the sum of `n` identical MAPs.
static MatrixCell	MAM.map_sumind(MatrixCell[] MAPs)	Computes the Markovian Arrival Process (MAP) representing the sum of `n` independent MAPs.
static MatrixCell	MAM.map_super(MatrixCell MAPa, MatrixCell MAPb)	Creates a superposition of two Markovian Arrival Processes (MAPs) to form a new MAP.
static MatrixCell	MAM.map_timereverse(MatrixCell map)	Computes the time-reversed MAP of a given MAP.
static MatrixCell	MAM.mmap_compress(MatrixCell MMAP)	Compresses a Markovian Arrival Process with marked arrivals (MMAP) as a mixture of 2-state acyclic Markovian Arrival Processes (MAPs).
static MatrixCell	MAM.mmap_compress(MatrixCell MMAP, SolverOptions config)	Compresses a Markovian Arrival Process with marked arrivals (MMAP) based on the provided configuration options.
static MatrixCell	MAM.mmap_exponential(Matrix lambda)	Fits a Markovian Arrival Process with marked arrivals (MMAP) with a single state based on the given arrival rates for each job class.
static MatrixCell	MAM.mmap_exponential(Matrix lambda, int n)	Fits an order-n Markovian Arrival Process with marked arrivals (MMAP) based on the given arrival rates for each job class.
static MatrixCell	MAM.mmap_hide(MatrixCell MMAP, Matrix types)	Hides specified types of arrivals in a Markovian Arrival Process with marked arrivals (MMAP).
static MatrixCell	MAM.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	MAM.mmap_mixture(Matrix alpha, Map<Integer,MatrixCell> MAPs)	Creates a mixture of MMAPs using the given weights (alpha) and MAPs.
static MatrixCell	MAM.mmap_normalize(MatrixCell MMAP)	Normalizes a Markovian Arrival Process with marked arrivals (MMAP) to ensure feasibility.
static MatrixCell	MAM.mmap_rand(int order, int classes)	Generates a random MMAP (Marked Markovian Arrival Process) with a given order and number of classes.
static MatrixCell	MAM.mmap_scale(MatrixCell MMAP, Matrix M)	Changes the mean inter-arrival time of a Markovian Arrival Process with marked arrivals (MMAP).
static MatrixCell	MAM.mmap_shorten(MatrixCell mmap)	Converts an MMAP representation from M3A format to BUTools format.
static MatrixCell	MAM.mmap_super(MatrixCell MMAPa)	Combines a list of MMAPs into one superposed MMAP.
static MatrixCell	MAM.mmap_super(MatrixCell MMAPa, MatrixCell MMAPb)	Combines two MMAPs into one superposed MMAP using the default option.
static MatrixCell	MAM.mmap_super(MatrixCell MMAPa, MatrixCell MMAPb, String opt)	Combines two MMAPs into one superposed MMAP.
static MatrixCell	MAM.mmap_super_safe(Map<Integer,MatrixCell> MMAPS, int maxorder)	Safely combines multiple MMAPs into a single superposed MMAP using the default method, while considering order constraints.
static MatrixCell	MAM.mmap_super_safe(Map<Integer,MatrixCell> MMAPS, int maxorder, String method)	Safely combines multiple MMAPs into a single superposed MMAP while considering order constraints.
static MatrixCell	MAM.mmap_timereverse(MatrixCell mmap)	Computes the time-reversed version of a Markovian Arrival Process with marked arrivals (MMAP).
static MatrixCell	MAM.mmpp2_fit(double E1, double E2, double E3, double G2)	Fits a 2-phase Markovian Arrival Process (MMPP2) to match the given first three moments and a fourth parameter G2.
static MatrixCell	MAM.mmpp2_fit1(double mean, double scv, double skew, double idc)	Fits a 2-phase Markov Modulated Poisson Process (MMPP2) based on the specified parameters.
static MatrixCell	NPFQN.npfqn_traffic_merge(Map<Integer,MatrixCell> MMAPa, String config_merge_, String config_compress_)	Merges MMAP traffic flows with specified configurations.
static MatrixCell	NPFQN.npfqn_traffic_merge_cs(Map<Integer,MatrixCell> MMAPs, Matrix prob)	Merges MMAP traffic flows with class switching using default parameters.
static MatrixCell	NPFQN.npfqn_traffic_merge_cs(Map<Integer,MatrixCell> MMAPs, Matrix prob, String config)	Merges MMAP traffic flows with class switching.

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

Modifier and Type	Method	Description
static Map<Integer,MatrixCell>	MAM.aph2_fitall(double M1, double M2, double M3)	Fits a set of acyclic phase-type (APH) distributions with two phases (APH(2)) to match the given moments of a random variable.
static Map<Integer,MatrixCell>	MAM.mmap_maps(MatrixCell MMAP)	Extracts K Markovian Arrival Processes (MAPs) from a given MMAP, one for each class.
static Map<Integer,MatrixCell>	NPFQN.npfqn_traffic_split_cs(MatrixCell MMAP, Matrix P)	Splits MMAP traffic flows with class switching.
static Map<Integer,Map<Integer,MatrixCell>>	MAM.ph_reindex(Map<Station,Map<JobClass,MatrixCell>> PHs, NetworkStruct sn)	Reindexes a map of phase-type (PH) distributions for a network model based on station and job class indices.

Methods in jline.api with parameters of type MatrixCell

Modifier and Type	Method	Description
static Ret.cacheMissRayInt	CACHE.cache_miss_rayint(Matrix gamma, Matrix m, MatrixCell lambda)	Estimates the cache miss rate and related metrics using the ray method for PDEs.
static MatrixCell	MAM.mamap2m_fit_gamma_fb_mmap(MatrixCell mmap)
static Matrix	MAM.map_acf(MatrixCell MAP)	Computes the autocorrelation function (ACF) for a given MAP using a default lag of 1.
static Matrix	MAM.map_acf(MatrixCell MAP, Matrix lags)	Computes the autocorrelation function (ACF) for a given MAP at multiple lags using a MatrixCell.
static double[]	MAM.map_acfc(MatrixCell MAP, int[] lags, double u)	Computes the autocorrelation function coefficients (ACFC) for a MAP counting process using a MatrixCell.
static Matrix	MAM.map_cdf(MatrixCell MAP, Matrix points)	Computes the cumulative distribution function (CDF) of the inter-arrival times of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static boolean	MAM.map_checkfeasible(MatrixCell MAP, double TOL)	Placeholder method to check the feasibility of a MAP.
double	MAM.map_count_mean(MatrixCell MAP, double t)	Computes the mean of the counting process over a specified interval length for a given Markovian Arrival Process (MAP).
double[]	MAM.map_count_mean(MatrixCell MAP, double[] t)	Computes the mean of the counting process over multiple specified interval lengths for a given Markovian Arrival Process (MAP).
double	MAM.map_count_var(MatrixCell MAP, double t)	Computes the variance of the counting process over a specified interval length for a given Markovian Arrival Process (MAP).
double[]	MAM.map_count_var(MatrixCell MAP, double[] t)	Computes the variance of the counting process over multiple specified interval lengths for a given Markovian Arrival Process (MAP).
static Matrix	MAM.map_embedded(MatrixCell MAP)	Computes the embedded discrete-time Markov chain (DTMC) matrix of a MAP given as a MatrixCell.
static double	MAM.map_gamma(MatrixCell MAP)	Computes the gamma parameter for a MAP using a MatrixCell.
static double[]	MAM.map_gamma2(MatrixCell MAP)	Returns the largest non-unit eigenvalue (both real and imaginary parts) of the embedded Discrete-Time Markov Chain (DTMC) of a given Markovian Arrival Process (MAP).
static double	MAM.map_idc(MatrixCell MAP)	Computes the asymptotic index of dispersion (IDC) for a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static Matrix	MAM.map_infgen(MatrixCell MAP)	Computes the infinitesimal generator matrix (Q) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static boolean	MAM.map_isfeasible(MatrixCell MAP)	Checks if the provided MAP is feasible using a default tolerance.
static boolean	MAM.map_isfeasible(MatrixCell MAP, double TOL)	Checks if the provided MAP is feasible based on the given tolerance.
static double	MAM.map_lambda(MatrixCell MAP)	Computes the arrival rate (lambda) of a Markovian Arrival Process (MAP) using matrices stored in a MatrixCell.
static MatrixCell	MAM.map_mark(MatrixCell MAP, Matrix prob)	Creates a Marked Markovian Arrival Process (MMAP) by marking a given Markovian Arrival Process (MAP) with additional phases based on specified marking probabilities.
static double	MAM.map_mean(MatrixCell MAP)	Computes the mean inter-arrival time of a Markovian Arrival Process (MAP) using matrices stored in a MatrixCell.
static double	MAM.map_moment(MatrixCell MAP, int order)	Computes the raw moments of the inter-arrival times of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static MatrixCell	MAM.map_normalize(MatrixCell MAP)	Sanitizes the (D0, D1) matrices of a Markovian Arrival Process (MAP) stored in a MatrixCell.
static Matrix	MAM.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	MAM.map_piq(MatrixCell MAP)	Computes the steady-state vector (pi) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
static double[]	MAM.map_sample(MatrixCell MAP, 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	MAM.map_scale(MatrixCell MAP, double newMean)	Rescales the mean inter-arrival time of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static double	MAM.map_scv(MatrixCell MAP)	Computes the squared coefficient of variation (SCV) of the inter-arrival times of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
static double	MAM.map_skew(MatrixCell MAP)	Computes the skewness of the inter-arrival times for a MAP using a MatrixCell.
static MatrixCell	MAM.map_sum(MatrixCell MAP, int n)	Computes the Markovian Arrival Process (MAP) representing the sum of `n` identical MAPs.
static MatrixCell	MAM.map_sumind(MatrixCell[] MAPs)	Computes the Markovian Arrival Process (MAP) representing the sum of `n` independent MAPs.
static MatrixCell	MAM.map_super(MatrixCell MAPa, MatrixCell MAPb)	Creates a superposition of two Markovian Arrival Processes (MAPs) to form a new MAP.
static MatrixCell	MAM.map_timereverse(MatrixCell map)	Computes the time-reversed MAP of a given MAP.
static double	MAM.map_var(MatrixCell MAP)	Computes the variance of the inter-arrival times for a MAP using a MatrixCell.
static double	MAM.map_varcount(MatrixCell MAP, double t)	Computes the variance of the counts in a MAP over a time period t using a MatrixCell.
static Matrix	MAM.map_varcount(MatrixCell MAP, Matrix t)	Computes the variance of the counts in a MAP over multiple time periods using a MatrixCell.
static Matrix	MAM.mmap_backward_moment(MatrixCell MMAP, Matrix ORDERS)	Computes the backward moments of an MMAP for specified orders with normalization.
static Matrix	MAM.mmap_backward_moment(MatrixCell MMAP, Matrix ORDERS, int NORM)	Computes the backward moments of an MMAP for specified orders.
static MatrixCell	MAM.mmap_compress(MatrixCell MMAP)	Compresses a Markovian Arrival Process with marked arrivals (MMAP) as a mixture of 2-state acyclic Markovian Arrival Processes (MAPs).
static MatrixCell	MAM.mmap_compress(MatrixCell MMAP, SolverOptions config)	Compresses a Markovian Arrival Process with marked arrivals (MMAP) based on the provided configuration options.
static Matrix	MAM.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	MAM.mmap_count_lambda(MatrixCell mmap)	Computes the arrival rate vector of the counting process for the given Marked MAP (MMAP).
static Matrix	MAM.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	MAM.mmap_count_var(MatrixCell MMAP, double t)	Computes the variance of the count vector of events of different types in a Markovian Arrival Process with marked arrivals (MMAP) over a time period.
static Matrix	MAM.mmap_cross_moment(MatrixCell mmap, int k)	Computes the k-th cross-moment matrix for a given MMAP.
static Matrix	MAM.mmap_forward_moment(MatrixCell MMAP, Matrix ORDERS)	Computes the forward moments of an MMAP for specified orders with normalization.
static Matrix	MAM.mmap_forward_moment(MatrixCell MMAP, Matrix ORDERS, int NORM)	Computes the forward moments of an MMAP for specified orders.
static MatrixCell	MAM.mmap_hide(MatrixCell MMAP, Matrix types)	Hides specified types of arrivals in a Markovian Arrival Process with marked arrivals (MMAP).
static Matrix	MAM.mmap_idc(MatrixCell MMAP)	Computes the asymptotic index of dispersion for counts (IDC) for a Markovian Arrival Process with marked arrivals (MMAP).
static boolean	MAM.mmap_isfeasible(MatrixCell MMAP)	Checks the feasibility of a Markovian Arrival Process with marked arrivals (MMAP).
static Matrix	MAM.mmap_lambda(MatrixCell MMAP)	Alias for mmap_count_lambda.
static Map<Integer,MatrixCell>	MAM.mmap_maps(MatrixCell MMAP)	Extracts K Markovian Arrival Processes (MAPs) from a given MMAP, one for each class.
static MatrixCell	MAM.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 Ret.mamMMAPMixtureFit	MAM.mmap_mixture_fit_mmap(MatrixCell mmap)	Fits a mixture of Markovian Arrival Processes (MMAPs) to match the given moments.
static MatrixCell	MAM.mmap_normalize(MatrixCell MMAP)	Normalizes a Markovian Arrival Process with marked arrivals (MMAP) to ensure feasibility.
static Matrix	MAM.mmap_pc(MatrixCell MMAP)	Computes the proportion of counts (PC) for each type in a Markovian Arrival Process with marked arrivals (MMAP).
static Ret.mamMMAPSample	MAM.mmap_sample(MatrixCell MMAP, long n)	Generates samples of inter-arrival times and event types from a MMAP using a specified number of samples.
static Ret.mamMMAPSample	MAM.mmap_sample(MatrixCell MMAP, long n, Random random)	Generates samples of inter-arrival times and event types from a MMAP using a specified number of samples and a random generator.
static MatrixCell	MAM.mmap_scale(MatrixCell MMAP, Matrix M)	Changes the mean inter-arrival time of a Markovian Arrival Process with marked arrivals (MMAP).
static MatrixCell	MAM.mmap_shorten(MatrixCell mmap)	Converts an MMAP representation from M3A format to BUTools format.
static Map<Integer[],Matrix>	MAM.mmap_sigma2(MatrixCell mmap)	Computes the second-order sigma values (covariances) for a given MMAP.
static MatrixCell	MAM.mmap_super(MatrixCell MMAPa)	Combines a list of MMAPs into one superposed MMAP.
static MatrixCell	MAM.mmap_super(MatrixCell MMAPa, MatrixCell MMAPb)	Combines two MMAPs into one superposed MMAP using the default option.
static MatrixCell	MAM.mmap_super(MatrixCell MMAPa, MatrixCell MMAPb, String opt)	Combines two MMAPs into one superposed MMAP.
static MatrixCell	MAM.mmap_timereverse(MatrixCell mmap)	Computes the time-reversed version of a Markovian Arrival Process with marked arrivals (MMAP).
static Map<Integer,MatrixCell>	NPFQN.npfqn_traffic_split_cs(MatrixCell MMAP, Matrix P)	Splits MMAP traffic flows with class switching.
static Ret.pfqnCore	PFQN.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.pfqn_conwayms_estimate(int M, int R, Matrix N_1, int[] nservers, Matrix Q, Matrix P, Matrix PB, MatrixCell Delta, Matrix W)
static Ret.pfqnForwardMVA	PFQN.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 double[]	POLLING.polling_qsys_1limited(MatrixCell[] arvMAPs, MatrixCell[] svcMAPs, MatrixCell[] switchMAPs)	Computes the exact mean waiting time solution for a polling system with open arrivals.
static double[]	POLLING.polling_qsys_exhaustive(MatrixCell[] arvMAPs, MatrixCell[] svcMAPs, MatrixCell[] switchMAPs)	Computes the exact mean waiting time solution for a polling system with open arrivals, where all queues are served exhaustively.
static double[]	POLLING.polling_qsys_gated(MatrixCell[] arvMAPs, MatrixCell[] svcMAPs, MatrixCell[] switchMAPs)	Computes the exact mean waiting time solution for a polling system with open arrivals, where all queues use gated service discipline.

Method parameters in jline.api with type arguments of type MatrixCell

Modifier and Type	Method	Description
static MatrixCell	MAM.mmap_mixture(Matrix alpha, Map<Integer,MatrixCell> MAPs)	Creates a mixture of MMAPs using the given weights (alpha) and MAPs.
static MatrixCell	MAM.mmap_super_safe(Map<Integer,MatrixCell> MMAPS, int maxorder)	Safely combines multiple MMAPs into a single superposed MMAP using the default method, while considering order constraints.
static MatrixCell	MAM.mmap_super_safe(Map<Integer,MatrixCell> MMAPS, int maxorder, String method)	Safely combines multiple MMAPs into a single superposed MMAP while considering order constraints.
static MatrixCell	NPFQN.npfqn_traffic_merge(Map<Integer,MatrixCell> MMAPa, String config_merge_, String config_compress_)	Merges MMAP traffic flows with specified configurations.
static MatrixCell	NPFQN.npfqn_traffic_merge_cs(Map<Integer,MatrixCell> MMAPs, Matrix prob)	Merges MMAP traffic flows with class switching using default parameters.
static MatrixCell	NPFQN.npfqn_traffic_merge_cs(Map<Integer,MatrixCell> MMAPs, Matrix prob, String config)	Merges MMAP traffic flows with class switching.
static Map<Integer,Map<Integer,MatrixCell>>	MAM.ph_reindex(Map<Station,Map<JobClass,MatrixCell>> PHs, NetworkStruct sn)	Reindexes a map of phase-type (PH) distributions for a network model based on station and job class indices.

Uses of MatrixCell in jline.io

Fields in jline.io declared as MatrixCell

Modifier and Type	Field	Description
MatrixCell	Ret.mamAPH2Fit.APH
MatrixCell	Ret.mamMAPFitReturn.MAP
MatrixCell	Ret.mamMMAPMixtureFit.MMAP
final MatrixCell	Ret.pfqnEstimate.P_1
final MatrixCell	Ret.pfqnEstimate.Q_1

Fields in jline.io with type parameters of type MatrixCell

Modifier and Type	Field	Description
Map<Integer,MatrixCell>	Ret.mamAPH2Fit.APHS
Map<Integer[],MatrixCell>	Ret.mamMMAPMixtureFit.PHs

Constructors in jline.io with parameters of type MatrixCell

Modifier	Constructor	Description
	pfqnEstimate(MatrixCell Q_1, MatrixCell P_1, Matrix PB_1, Matrix T_1)

Uses of MatrixCell in jline.lang

Fields in jline.lang declared as MatrixCell

Modifier and Type	Field	Description
MatrixCell[]	Env.holdTime
MatrixCell[][]	Env.proc

Fields in jline.lang with type parameters of type MatrixCell

Modifier and Type	Field	Description
Map<Mode,MatrixCell>	NodeParam.firingproc
Map<Station,Map<JobClass,MatrixCell>>	NetworkStruct.proc

Uses of MatrixCell in jline.lang.processes

Fields in jline.lang.processes declared as MatrixCell

Modifier and Type	Field	Description
protected MatrixCell	Markovian.process

Methods in jline.lang.processes that return MatrixCell

Modifier and Type	Method	Description
MatrixCell	MAP.getProcess()
MatrixCell	MarkedMMPP.getProcess()
MatrixCell	Markovian.getProcess()
MatrixCell	PH.getProcess()
MatrixCell	MAP.getRenewalProcess()

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

Modifier and Type	Method	Description
void	Markovian.setProcess(MatrixCell D)

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

Modifier	Constructor	Description
	MAP(MatrixCell map)
	MarkedMAP(MatrixCell mmap)
	MarkedMMPP(MatrixCell mmap)

Uses of MatrixCell in jline.lib.thirdparty

Methods in jline.lib.thirdparty with parameters of type MatrixCell

Modifier and Type	Method	Description
static Map<String,Map<Integer,Matrix>>	BUTOOLS.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>>	BUTOOLS.MMAPPH1NPPR(MatrixCell D, MatrixCell sigma, MatrixCell S, Integer numOfQLMoms, Integer numOfQLProbs, Integer numOfSTMoms, Matrix stCdfPoints, Double prec, Integer erlMaxOrder_, Matrix classes_)

Uses of MatrixCell in jline.solvers.mam

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

Modifier and Type	Method	Description
Map<Integer,MatrixCell>	SolverMAM.solver_mam_passage_time(NetworkStruct sn, Map<Integer,Map<Integer,MatrixCell>> PH)

Method parameters in jline.solvers.mam with type arguments of type MatrixCell

Modifier and Type	Method	Description
Map<Integer,MatrixCell>	SolverMAM.solver_mam_passage_time(NetworkStruct sn, Map<Integer,Map<Integer,MatrixCell>> PH)

Uses of MatrixCell in jline.util

Fields in jline.util declared as MatrixCell

Modifier and Type	Field	Description
MatrixCell	PopulationLattice.sprodResult.D

Methods in jline.util with parameters of type MatrixCell

Modifier and Type	Method	Description
static PopulationLattice.sprodResult	PopulationLattice.sprod(Matrix s, Matrix S, MatrixCell D)

Constructors in jline.util with parameters of type MatrixCell

Modifier	Constructor	Description
	MatrixCell(MatrixCell x)
	sprodResult(Matrix s, Matrix n, Matrix S, MatrixCell D)