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M

M2M - class in jline.io
Model-to-Model transformation class for converting between different queueing network model formats.
M3A - class in jline.lib.m3a
M3A (Markovian Arrival Process with 3-moment Approximation) tool for MMAP compression.
M3A.Companion - class in jline.lib.m3a.M3A
 
M3A.CoxianParameters - class in jline.lib.m3a.M3A
 
M3A.ErlangParameters - class in jline.lib.m3a.M3A
 
M3A.HyperExpParameters - class in jline.lib.m3a.M3A
 
M3A.PhaseTypeParameters - class in jline.lib.m3a.M3A
 
m3afit_auto(jline.lib.m3a.MTrace,jline.lib.m3a.M3aFitOptions) - function in jline.lib.m3a.M3aFitKt
Automatic fitting of trace into a Marked Markovian Arrival Process.
m3afit_auto(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer,java.lang.Integer) - function in jline.lib.m3a.M3aFitKt
Automatic fitting with simple parameters.
m3afit_auto(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer) - function in jline.lib.m3a.M3aFitKt
Automatic fitting with simple parameters.
m3afit_init(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.m3a.M3aFitKt
Prepares multiclass trace for M3A fitting from Matrix inputs.
m3afit_init(kotlin.DoubleArray,kotlin.IntArray) - function in jline.lib.m3a.M3aFitKt
Prepares multiclass trace for M3A fitting.
M3aFitKt - class in jline.lib.m3a
 
M3aFitOptions - class in jline.lib.m3a
Options for M3A fitting algorithms.
M3aUtils - class in jline.lib.m3a
Utility functions for M3A (Markovian Arrival Process with 3-moment Approximation) compression.
M3aUtils.Companion - class in jline.lib.m3a.M3aUtils
 
M3pp22_fitc_approx_cov - class in jline.api.mam.m3pp
Fits a second-order Marked MMPP for two classes using covariance approximation.
m3pp22_fitc_approx_cov(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp22_fitc_approx_cov.Companion
 
M3pp22_fitc_approx_cov_multiclass - class in jline.api.mam.m3pp
Fits a M3PP(2,2) given the underlying MMPP(2).
m3pp22_fitc_approx_cov_multiclass(kotlin.Array,kotlin.DoubleArray,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp22_fitc_approx_cov_multiclass.Companion
 
m3pp22_interleave_fitc(kotlin.Array,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp22_interleave_fitcKt
Fits L pairs of classes into a single MMAP, obtained by lumped superposition of L different M3PP2 processes.
M3pp22_interleave_fitcKt - class in jline.api.mam.m3pp
 
M3pp22FitCountApproxCovAlgo - class in jline.api.mam.m3pp
M3Pp22 Fit Count Approx Cov algorithms
M3pp22FitCountApproxCovMulticlassAlgo - class in jline.api.mam.m3pp
M3Pp22 Fit Count Approx Cov Multiclass algorithms
M3pp22InterleaveFitCountAlgo - class in jline.api.mam.m3pp
M3Pp22 Interleave Fit Count algorithms
M3pp2m_fitc - class in jline.api.mam.m3pp
Fits a second-order Marked MMPP using exact count statistics.
m3pp2m_fitc(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc.Companion
 
m3pp2m_fitc(kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray) - function in jline.api.mam.m3pp.M3pp2m_fitcKt
Simple wrapper function for m3pp2m_fitc
M3pp2m_fitc_approx - class in jline.api.mam.m3pp
Fits a second-order Marked MMPP using approximation with optimization.
m3pp2m_fitc_approx(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_approx.Companion
 
M3pp2m_fitc_approx_ag - class in jline.api.mam.m3pp
Fits a second-order Marked MMPP using auto-gamma approach.
m3pp2m_fitc_approx_ag(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_approx_ag.Companion
 
m3pp2m_fitc_approx_ag_multiclass(kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray) - function in jline.api.mam.m3pp.M3pp2m_fitcKt
Wrapper function for m3pp2m_fitc_approx_ag_multiclass
M3pp2m_fitc_approx_ag_multiclass - class in jline.api.mam.m3pp
Fits a M3PP(2,m) given the underlying MMPP(2).
m3pp2m_fitc_approx_ag_multiclass(kotlin.Array,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_approx_ag_multiclass.Companion
 
m3pp2m_fitc_theoretical(jline.util.matrix.MatrixCell,java.lang.String,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_theoreticalKt
Fits the theoretical characteristics of a MMAP(n,m) with a M3PP(2,m).
m3pp2m_fitc_theoretical(jline.util.matrix.MatrixCell,java.lang.String,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_theoreticalKt
Fits the theoretical characteristics of a MMAP(n,m) with a M3PP(2,m).
m3pp2m_fitc_theoretical(jline.util.matrix.MatrixCell,java.lang.String) - function in jline.api.mam.m3pp.M3pp2m_fitc_theoreticalKt
Fits the theoretical characteristics of a MMAP(n,m) with a M3PP(2,m).
m3pp2m_fitc_theoretical(jline.util.matrix.MatrixCell) - function in jline.api.mam.m3pp.M3pp2m_fitc_theoreticalKt
Fits the theoretical characteristics of a MMAP(n,m) with a M3PP(2,m).
M3pp2m_fitc_theoreticalKt - class in jline.api.mam.m3pp
 
m3pp2m_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.String,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using Matrix inputs.
m3pp2m_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.String,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using Matrix inputs.
m3pp2m_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.String) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using Matrix inputs.
m3pp2m_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using Matrix inputs.
m3pp2m_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.String,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using counting process characteristics.
m3pp2m_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.String,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using counting process characteristics.
m3pp2m_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.String) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using counting process characteristics.
m3pp2m_fitc_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Fits a M3PP(2,m) from trace data using counting process characteristics.
M3pp2m_fitc_traceKt - class in jline.api.mam.m3pp
 
M3pp2m_fitcKt - class in jline.api.mam.m3pp
 
m3pp2m_interleave(java.util.List) - function in jline.api.mam.m3pp.M3pp2m_interleaveKt
Computes the interleaved MMAP obtained by multiple M3PP(2,m).
M3pp2m_interleaveKt - class in jline.api.mam.m3pp
 
M3pp2mFitCountAlgo - class in jline.api.mam.m3pp
M3Pp2M Fit Count algorithms
M3pp2mFitCountApproxAgAlgo - class in jline.api.mam.m3pp
M3Pp2M Fit Count Approx Ag algorithms
M3pp2mFitCountApproxAgMulticlassAlgo - class in jline.api.mam.m3pp
M3Pp2M Fit Count Approx Ag Multiclass algorithms
M3pp2mFitCountApproxAlgo - class in jline.api.mam.m3pp
M3Pp2M Fit Count Approx algorithms
M3pp2mFitcTheoreticalAlgo - class in jline.api.mam.m3pp
M3PP 2m fitc theoretical algorithms
M3pp2mFitcTraceAlgo - class in jline.api.mam.m3pp
M3PP 2m fitc trace algorithms
M3pp2mInterleaveAlgo - class in jline.api.mam.m3pp
M3Pp2M Interleave algorithms
m3pp_interleave_fitc(kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.Array,kotlin.Array,java.lang.Double,java.lang.Double,kotlin.IntArray,java.lang.Boolean) - function in jline.api.mam.m3pp.M3pp_interleave_fitcKt
Fits k second-order M3PPm_j and interleaves them into a M3PPm of order k+1, with m = sum_j=1^k m_j.
m3pp_interleave_fitc_theoretical(jline.util.matrix.MatrixCell,java.lang.Double,java.lang.Double,kotlin.Array) - function in jline.api.mam.m3pp.M3pp_interleave_fitc_theoreticalKt
Interleaves k M3PP to fit a multi-class MMAP using theoretical characteristics.
M3pp_interleave_fitc_theoreticalKt - class in jline.api.mam.m3pp
 
m3pp_interleave_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.Double,java.lang.Double,kotlin.Array) - function in jline.api.mam.m3pp.M3pp_interleave_fitc_traceKt
Interleaves k M3PP to fit a multi-class trace with m classes.
M3pp_interleave_fitc_traceKt - class in jline.api.mam.m3pp
 
M3pp_interleave_fitcKt - class in jline.api.mam.m3pp
 
m3pp_rand(java.lang.Integer,java.lang.Integer,java.lang.Long) - function in jline.api.mam.m3pp.M3pp_randKt
Generates a random M3PP (Markovian Multi-class Point Process) with specified order and number of classes.
m3pp_rand_targeted(java.lang.Integer,java.lang.Integer,java.lang.Double,java.lang.Double,java.lang.Long) - function in jline.api.mam.m3pp.M3pp_randKt
Generates a random M3PP with specific characteristics.
M3pp_randKt - class in jline.api.mam.m3pp
 
m3pp_superpos_fitc(kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitcKt
Fits k second-order M3PPm_j and superposes them into a M3PPm of order k+1, with m = sum_j=1^k m_j.
m3pp_superpos_fitc(kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k individual M3PP processes.
m3pp_superpos_fitc_theoretical(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_theoreticalKt
Fits k second-order M3PPm_j and superposes them into a M3PPm using theoretical count characteristics of the target process.
M3pp_superpos_fitc_theoreticalKt - class in jline.api.mam.m3pp
 
m3pp_superpos_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_theoreticalKt
Fits k second-order M3PPm_j and superposes them using trace data to determine theoretical characteristics.
m3pp_superpos_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k M3PP processes to fit a multi-class trace from Matrix inputs.
m3pp_superpos_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k M3PP processes to fit a multi-class trace from Matrix inputs.
m3pp_superpos_fitc_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k M3PP processes to fit a multi-class trace from Matrix inputs.
m3pp_superpos_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.Double,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k M3PP processes to fit a multi-class trace with m classes.
m3pp_superpos_fitc_trace(kotlin.DoubleArray,kotlin.IntArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k M3PP processes to fit a multi-class trace with m classes.
m3pp_superpos_fitc_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.m3pp.M3pp_superpos_fitc_traceKt
Superposes k M3PP processes to fit a multi-class trace with m classes.
M3pp_superpos_fitc_traceKt - class in jline.api.mam.m3pp
 
M3pp_superpos_fitcKt - class in jline.api.mam.m3pp
 
M3ppInterleaveFitCountAlgo - class in jline.api.mam.m3pp
M3Pp Interleave Fit Count algorithms
M3ppInterleaveFitCountTheoreticalAlgo - class in jline.api.mam.m3pp
M3Pp Interleave Fit Count Theoretical algorithms
M3ppInterleaveFitCountTraceAlgo - class in jline.api.mam.m3pp
M3Pp Interleave Fit Count Trace algorithms
M3ppRandAlgo - class in jline.api.mam.m3pp
M3Pp Rand algorithms
M3ppSuperposFitCountAlgo - class in jline.api.mam.m3pp
M3Pp Superpos Fit Count algorithms
M3ppSuperposFitCountTheoreticalAlgo - class in jline.api.mam.m3pp
M3Pp Superpos Fit Count Theoretical algorithms
M3ppSuperposFitcTraceAlgo - class in jline.api.mam.m3pp
M3PP superposition fitc trace algorithms
main(kotlin.Array) - function in jline.bench.AllBench
 
main(kotlin.Array) - function in jline.bench.QuickBenchTest
 
main(kotlin.Array) - function in jline.bench.cqn.BenchCQN_FCFS
 
main(kotlin.Array) - function in jline.bench.cqn.BenchCQN_PS
 
main(kotlin.Array) - function in jline.bench.cqn.BenchCQN_RM
Main method with command line options
main(kotlin.Array) - function in jline.bench.fj.BenchFJ_Closed
 
main(kotlin.Array) - function in jline.bench.fj.BenchFJ_FCFS
 
main(kotlin.Array) - function in jline.bench.fj.BenchFJ_Mixed
 
main(kotlin.Array) - function in jline.bench.fj.BenchFJ_Nested
 
main(kotlin.Array) - function in jline.bench.fj.BenchFJ_Open
 
main(kotlin.Array) - function in jline.bench.fj.BenchFJ_PS
 
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_Custom
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_Default
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_Fluid
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_LQNS
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_MVA
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_NC
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.BenchLQN_SRVN
Main method for testing
main(kotlin.Array) - function in jline.bench.lqn.SimpleLQNBenchmark
Main method for testing
main(kotlin.Array) - function in jline.bench.mqn.BenchMQN_FCFS
 
main(kotlin.Array) - function in jline.bench.mqn.BenchMQN_PS
 
main(kotlin.Array) - function in jline.bench.oqn.BenchOQN_FCFS
 
main(kotlin.Array) - function in jline.bench.oqn.BenchOQN_PS
 
main(kotlin.Array) - function in jline.cli.LineCLI
Main entry point for the LINE CLI
main(kotlin.Array) - function in jline.cli.LineWebSocketClient
The main method, which serves as the entry point for the program.
main(kotlin.Array) - function in jline.cli.LineWebSocketServer
The main method, which serves as the entry point for the server application.
main(kotlin.Array) - function in jline.examples.NetworkGeneratorExample
 
main(kotlin.Array) - function in jline.examples.java.AdvancedExamples
 
main(kotlin.Array) - function in jline.examples.java.AllExamples
 
main(kotlin.Array) - function in jline.examples.java.BasicExamples
 
main(kotlin.Array) - function in jline.examples.java.GettingStarted
Main method for testing and demonstrating getting started examples.
main(kotlin.Array) - function in jline.examples.java.advanced.AgentModelExamples
Run all agent model examples.
main(kotlin.Array) - function in jline.examples.java.advanced.BASBlockingDebugTest
 
main(kotlin.Array) - function in jline.examples.java.advanced.CDFRespTExamples
Main method to run all CDF response time examples.
main(kotlin.Array) - function in jline.examples.java.advanced.CDFRespTModel
Main method for testing and demonstrating response time CDF examples.
main(kotlin.Array) - function in jline.examples.java.advanced.CyclicPollingExamples
Main method to run all cyclic polling examples.
main(kotlin.Array) - function in jline.examples.java.advanced.CyclicPollingModel
Main method for testing and demonstrating cyclic polling examples.
main(kotlin.Array) - function in jline.examples.java.advanced.EnvBreakdownExample
Main method to run all examples.
main(kotlin.Array) - function in jline.examples.java.advanced.FCRegionExamples
 
main(kotlin.Array) - function in jline.examples.java.advanced.InitStateExamples
Main method to run all initial state examples.
main(kotlin.Array) - function in jline.examples.java.advanced.LayeredCQExamples
Main method to run all layered CQ examples.
main(kotlin.Array) - function in jline.examples.java.advanced.LoadDependentExamples
Main method to run all load-dependent examples.
main(kotlin.Array) - function in jline.examples.java.advanced.LoadDependentModel
Main method for testing and demonstrating load-dependent examples.
main(kotlin.Array) - function in jline.examples.java.advanced.RandomEnvExamples
Main method to run all random environment examples.
main(kotlin.Array) - function in jline.examples.java.advanced.RandomEnvironmentModel
Main method for testing and demonstrating random environment examples.
main(kotlin.Array) - function in jline.examples.java.advanced.StateDepRoutingExamples
Main method to run all state-dependent routing examples.
main(kotlin.Array) - function in jline.examples.java.advanced.StateDepRoutingModel
Main method for testing and demonstrating state-dependent routing examples.
main(kotlin.Array) - function in jline.examples.java.advanced.StateProbabilitiesExamples
Main method to run all state probability examples.
main(kotlin.Array) - function in jline.examples.java.advanced.StateProbabilitiesModel
Main method for testing and demonstrating state probability examples.
main(kotlin.Array) - function in jline.examples.java.advanced.SwitchoverTimesExamples
Main method to run all switchover time examples.
main(kotlin.Array) - function in jline.examples.java.advanced.SwitchoverTimesModel
Main method for testing and demonstrating switchover times examples.
main(kotlin.Array) - function in jline.examples.java.basic.CacheExamples
 
main(kotlin.Array) - function in jline.examples.java.basic.CacheModel
Main method for testing and demonstrating cache model examples.
main(kotlin.Array) - function in jline.examples.java.basic.ClassSwitchExamples
 
main(kotlin.Array) - function in jline.examples.java.basic.ClassSwitchingModel
Main method for testing and demonstrating class switching examples.
main(kotlin.Array) - function in jline.examples.java.basic.ClosedExamples
Main method demonstrating all closed queueing network examples.
main(kotlin.Array) - function in jline.examples.java.basic.ClosedModel
Main method for testing and demonstrating closed model examples.
main(kotlin.Array) - function in jline.examples.java.basic.ForkJoinExamples
Main method demonstrating all fork-join examples.
main(kotlin.Array) - function in jline.examples.java.basic.ForkJoinModel
Main method for testing and demonstrating fork-join model examples.
main(kotlin.Array) - function in jline.examples.java.basic.LayeredExamples
Main method demonstrating selected layered network examples.
main(kotlin.Array) - function in jline.examples.java.basic.LayeredModel
Main method for testing and demonstrating layered model examples.
main(kotlin.Array) - function in jline.examples.java.basic.MixedExamples
Main method demonstrating all mixed queueing network examples.
main(kotlin.Array) - function in jline.examples.java.basic.MixedModel
Main method for testing and demonstrating mixed model examples.
main(kotlin.Array) - function in jline.examples.java.basic.OpenExamples
Main method demonstrating all open queueing network examples.
main(kotlin.Array) - function in jline.examples.java.basic.OpenModel
Main method for testing and demonstrating open model examples.
main(kotlin.Array) - function in jline.examples.java.basic.PrioExamples
Main method demonstrating all priority queueing examples.
main(kotlin.Array) - function in jline.examples.java.basic.PrioModel
Main method for testing and demonstrating priority examples.
main(kotlin.Array) - function in jline.examples.java.basic.StochPetriNetExamples
Main method demonstrating selected Petri net examples.
main(kotlin.Array) - function in jline.examples.java.basic.StochPetriNetModel
Main method for testing and demonstrating stochastic Petri net examples.
main(kotlin.Array) - function in jline.examples.java.models.Gallery
Main method for testing and demonstrating gallery examples.
main(kotlin.Array) - function in jline.io.REPL
Main method to start REPL
main(kotlin.Array) - function in jline.lang.processes.DiscreteSampler
 
main(kotlin.Array) - function in jline.lang.processes.Geometric
 
main(kotlin.Array) - function in jline.lang.processes.Poisson
 
main(kotlin.Array) - function in jline.lang.processes.Zipf
 
main(kotlin.Array) - function in jline.lib.lti.customromberg
 
main(kotlin.Array) - function in jline.lib.lti.euler
 
main(kotlin.Array) - function in jline.lib.lti.gaverstehfest
 
main() - function in jline.lib.mom.MainKt
 
main() - function in jline.lib.mom.SimpleExampleKt
 
main() - function in jline.lib.perm.PermExampleKt
Example usage of the permanent computation algorithms.
mainFJ(jline.lib.fjcodes.FJArrival,jline.lib.fjcodes.FJService,kotlin.DoubleArray,java.lang.Integer,java.lang.Integer,java.lang.String) - function in jline.lib.fjcodes.MainFJKt
Convenience overload for single K value
mainFJ(jline.lib.fjcodes.FJArrival,jline.lib.fjcodes.FJService,kotlin.DoubleArray,kotlin.IntArray,kotlin.IntArray,java.lang.String) - function in jline.lib.fjcodes.MainFJKt
Compute response time percentiles for K-node Fork-Join queueFor K=1: Uses exact MAP/PH/1 analysis For K=2: Uses approximation from Section 4 of the paper For K>2: Uses logarithmic extrapolation from K=1 and K=2 results
MainFJKt - class in jline.lib.fjcodes
 
MainKt - class in jline.lib.mom
 
MAM - enum entry in jline.lang.constant.SolverType
 
MAM - class in jline.solvers.mam
MAM is an alias for SolverMAM (Matrix Analytic Methods solver).
mama1() - function in jline.lib.kpctoolbox.MAPCatalog
MAMA1 - 2-state MAP model Source: mama1.
mama2() - function in jline.lib.kpctoolbox.MAPCatalog
MAMA2 - 2-state MAP model (variant of MAMA1) Source: mama2.
mama3() - function in jline.lib.kpctoolbox.MAPCatalog
MAMA3 - 2-state MAP model Source: mama3.
mama4() - function in jline.lib.kpctoolbox.MAPCatalog
MAMA4 - 2-state MAP model Source: mama4.
mama5() - function in jline.lib.kpctoolbox.MAPCatalog
MAMA5 - 2-state MAP model Source: mama5.
mamap22_fit_bs_multiclass(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Object,kotlin.DoubleArray) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) with backward moments (B) and sigma characteristics (S) for 2 classes.
mamap22_fit_fs_multiclass(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Object,kotlin.DoubleArray) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) with forward moments (F) and sigma characteristics (S) for 2 classes.
mamap22_fit_gamma_bs(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) with backward selection using gamma auto-correlation.
mamap22_fit_gamma_bs_mmap(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) from an existing MMAP using backward selection with gamma auto-correlation.
mamap22_fit_gamma_bs_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) from a marked trace using backward selection with gamma auto-correlation.
mamap22_fit_gamma_fs(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) with forward selection using gamma auto-correlation.
mamap22_fit_gamma_fs_mmap(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) from an existing MMAP using forward selection with gamma auto-correlation.
mamap22_fit_gamma_fs_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Mamap22_fit_gamma_fs_traceKt
Fits a MAMAP(2,2) using forward-start method from trace data.
mamap22_fit_gamma_fs_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mamap22_fit_multiclassKt
Fits MAMAP(2,2) from a marked trace using forward selection with gamma auto-correlation.
Mamap22_fit_gamma_fs_traceKt - class in jline.api.mam
 
Mamap22_fit_multiclassKt - class in jline.api.mam
 
Mamap22FitGammaFsTrace - class in jline.api.mam
MAMAP 22 fit gamma fs trace algorithms
Mamap22FitMulticlass - class in jline.api.mam
MAMAP 22 fit multiclass algorithms
mamap2m_can1_coefficients(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mamap2m_coefficientsKt
Returns the coefficients used in the direct and inverse formulas for fitting a MAMAP(2,m) in first canonical form (gamma 0).
mamap2m_can2_coefficients(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mamap2m_coefficientsKt
Returns the coefficients used in the direct and inverse formulas for fitting a MAMAP(2,m) in second canonical form (gamma < 0).
Mamap2m_coefficientsKt - class in jline.api.mam
 
Mamap2m_fit - class in jline.api.mam
Fits a MAMAP(2,m) (Markovian Arrival Process with Marked arrivals) that matches the provided characteristics.
mamap2m_fit(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,jline.util.matrix.Matrix,kotlin.DoubleArray) - function in jline.api.mam.Mamap2m_fit.Companion
 
mamap2m_fit(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,jline.util.matrix.Matrix) - function in jline.api.mam.Mamap2m_fit.Companion
 
mamap2m_fit_fb_multiclass(jline.util.matrix.MatrixCell,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray) - function in jline.api.mam.Mamap2m_fit_fb_multiclassKt
Performs approximate fitting of a MMAP given the underlying MAP, the class probabilities, forward moments, and backward moments.
Mamap2m_fit_fb_multiclassKt - class in jline.api.mam
 
mamap2m_fit_gamma_fb(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray) - function in jline.api.mam.Mamap2m_fit_gamma_fb_mmapKt
Computes the second-order MAMAPm fitting the given ordinary moments, autocorrelation decay rate, class probabilities, forward moments, and backward moments.
mamap2m_fit_gamma_fb_mmap(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mamap2m_fit_gamma_fb_mmapKt
Fits a second-order acyclic MMAPm to match the characteristics of the input MMAP.
Mamap2m_fit_gamma_fb_mmapKt - class in jline.api.mam
 
mamap2m_fit_gamma_fb_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mamap2m_fit_gamma_fb_traceKt
Performs approximate fitting of a marked trace from Matrix inputs.
mamap2m_fit_gamma_fb_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Mamap2m_fit_gamma_fb_traceKt
Performs approximate fitting of a marked trace, yielding a second-order acyclic MMAP that matches the class probabilities, the forward and backward moments.
Mamap2m_fit_gamma_fb_traceKt - class in jline.api.mam
 
mamap2m_fit_mmap(jline.util.matrix.MatrixCell,kotlin.DoubleArray) - function in jline.api.mam.Mamap2m_fit_mmapKt
Fits a MAPH(2,m) or MAMAP(2,m) that matches the characteristics of the input MMAP.
mamap2m_fit_mmap(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mamap2m_fit_mmapKt
Fits a MAPH(2,m) or MAMAP(2,m) that matches the characteristics of the input MMAP.
Mamap2m_fit_mmapKt - class in jline.api.mam
 
mamap2m_fit_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Mamap2m_fit_traceKt
Fits a MAMAP(2,m) to trace data.
Mamap2m_fit_traceKt - class in jline.api.mam
 
Mamap2mCoefficients - class in jline.api.mam
MAMAP 2m coefficients algorithms
Mamap2mFitAlgo - class in jline.api.mam
MAMAP 2m fit algorithms
Mamap2mFitFbMulticlassAlgo - class in jline.api.mam
MAMAP 2m fit fb multiclass algorithms
Mamap2mFitGammaFbMmapAlgo - class in jline.api.mam
MAMAP 2m fit gamma fb mmap algorithms
Mamap2mFitGammaFbTraceAlgo - class in jline.api.mam
MAMAP 2m fit gamma fb trace algorithms
Mamap2mFitMmapAlgo - class in jline.api.mam
MAMAP 2m fit mmap algorithms
Mamap2mFitTraceAlgo - class in jline.api.mam
MAMAP 2m fit trace algorithms
MAMFJResult - class in jline.solvers.mam
Result from Fork-Join analysis
MAMOptions - class in jline.solvers.mam
 
MAMResult - class in jline.solvers.mam
 
MAP - enum entry in jline.lang.constant.ProcessType
 
MAP - class in jline.lang.processes
A Markovian Arrival Process
map2_fit(java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Map2_fitKt
Fits a 2-phase Markovian Arrival Process (MAP2) using the first three moments.
map2_fit(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Map2_fitKt
Fits a 2-phase Markovian Arrival Process (MAP2) to match the given moments and decay rate of the autocorrelation function.
Map2_fitKt - class in jline.api.mam
 
map2CorrelationBounds(kotlin.DoubleArray) - function in jline.lib.butools.map.MAP2CorrelationBoundsKt
Returns the upper and lower correlation bounds for a MAP(2) given the three marginal moments.
MAP2CorrelationBoundsKt - class in jline.lib.butools.map
 
Map2FitAlgo - class in jline.api.mam
Map2 Fit algorithms
map2FromMoments(kotlin.DoubleArray,java.lang.Double) - function in jline.lib.butools.map.MAP2FromMomentsKt
Returns a MAP(2) which has the same 3 marginal moments and lag-1 autocorrelation as given.
MAP2FromMomentsKt - class in jline.lib.butools.map
 
map2mmpp(kotlin.Array) - function in jline.api.mam.Map2mmppKt
Convert a MAP to MMPP format by extracting generator matrix Q and rate matrix LAMBDA.
Map2mmppKt - class in jline.api.mam
 
map_acf(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_acfKt
Computes the autocorrelation function (ACF) for a given MAP using a default lag of 1.
map_acf(jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_acfKt
Computes the autocorrelation function (ACF) for a given MAP at multiple lags.
map_acf(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Map_acfKt
Computes the autocorrelation function (ACF) for a given MAP at a specific lag.
map_acf(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_acfKt
Computes the autocorrelation function (ACF) for a given MAP using a default lag of 1.
map_acf(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Map_acfKt
Computes the autocorrelation function (ACF) for a given MAP at multiple lags using a MatrixCell.
map_acfc(jline.util.matrix.Matrix,jline.util.matrix.Matrix,kotlin.IntArray,java.lang.Double) - function in jline.api.mam.Map_acfcKt
Computes the autocorrelation function coefficients (ACFC) for a MAP counting process.
map_acfc(jline.util.matrix.MatrixCell,kotlin.IntArray,java.lang.Double) - function in jline.api.mam.Map_acfcKt
Computes the autocorrelation function coefficients (ACFC) for a MAP counting process using a MatrixCell.
Map_acfcKt - class in jline.api.mam
 
Map_acfKt - class in jline.api.mam
 
map_block(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.String) - function in jline.api.mam.Map_blockKt
Constructs a MAP(2) or MAP(1) according to given moments and autocorrelation parameters.
Map_blockKt - class in jline.api.mam
 
map_ccdf_derivative(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Map_ccdf_derivativeKt
Compute derivative at 0 of a MAP complementary CDF
map_ccdf_derivative(jline.util.matrix.MatrixCell,java.lang.Integer) - function in jline.api.mam.Map_ccdf_derivativeKt
Compute derivative at 0 of a MAP complementary CDFBased on: A.
Map_ccdf_derivativeKt - class in jline.api.mam
 
map_cdf(jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_cdfKt
Computes the cumulative distribution function (CDF) of the inter-arrival times of a Markovian Arrival Process (MAP).
map_cdf(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Map_cdfKt
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.
Map_cdfKt - class in jline.api.mam
 
map_checkfeasible(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.api.mam.Map_checkfeasibleKt
Check the feasibility of a MAP given separate D0 and D1 matrices.
map_checkfeasible(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_checkfeasibleKt
Check the feasibility of a MAP given separate D0 and D1 matrices.
map_checkfeasible(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_checkfeasibleKt
Check the feasibility of a MAP with detailed validation.
Map_checkfeasibleKt - class in jline.api.mam
 
map_count_mean(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_count_meanKt
Computes the mean of the counting process over a specified interval length for a given Markovian Arrival Process (MAP).
map_count_mean(jline.util.matrix.MatrixCell,kotlin.DoubleArray) - function in jline.api.mam.Map_count_meanKt
Computes the mean of the counting process over multiple specified interval lengths for a given Markovian Arrival Process (MAP).
Map_count_meanKt - class in jline.api.mam
 
map_count_moment(jline.util.matrix.MatrixCell,java.lang.Double,java.lang.Integer) - function in jline.api.mam.Map_count_momentKt
Computes power moments of counts at resolution t for a Markovian Arrival Process (MAP).
map_count_moment(jline.util.matrix.MatrixCell,java.lang.Double,kotlin.IntArray) - function in jline.api.mam.Map_count_momentKt
Computes multiple power moments of counts at resolution t for a MAP.
Map_count_momentKt - class in jline.api.mam
 
map_count_var(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_count_varKt
Computes the variance of the counting process over a specified interval length for a given Markovian Arrival Process (MAP).
map_count_var(jline.util.matrix.MatrixCell,kotlin.DoubleArray) - function in jline.api.mam.Map_count_varKt
Computes the variance of the counting process over multiple specified interval lengths for a given Markovian Arrival Process (MAP).
Map_count_varKt - class in jline.api.mam
 
map_embedded(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_embeddedKt
Computes the embedded discrete-time Markov chain (DTMC) matrix of a MAP.
map_embedded(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_embeddedKt
Computes the embedded discrete-time Markov chain (DTMC) matrix of a MAP given as a MatrixCell.
Map_embeddedKt - class in jline.api.mam
 
map_erlang(java.lang.Double,java.lang.Integer) - function in jline.api.mam.Map_erlangKt
Fits an Erlang-k process as a Markovian Arrival Process (MAP).
Map_erlangKt - class in jline.api.mam
 
map_example1() - function in jline.lib.kpctoolbox.MAPCatalog
MAP Example 1 Source: MAP_example1.
map_exponential(java.lang.Double) - function in jline.api.mam.Map_exponentialKt
Creates a Markovian Arrival Process (MAP) with an exponential inter-arrival time distribution.
Map_exponentialKt - class in jline.api.mam
 
map_feasblock(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.String) - function in jline.api.mam.Map_feasblockKt
Fits the most similar feasible MAP when exact moment matching fails.
Map_feasblockKt - class in jline.api.mam
 
map_feastol() - function in jline.api.mam.Map_feastolKt
Returns the feasibility tolerance for MAPs.
Map_feastolKt - class in jline.api.mam
 
map_gamma(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_gammaKt
Computes the gamma parameter for a MAP, which is the autocorrelation decay rate.
map_gamma(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_gammaKt
Computes the gamma parameter for a MAP using a MatrixCell.
map_gamma2(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_gamma2Kt
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).
Map_gamma2Kt - class in jline.api.mam
 
Map_gammaKt - class in jline.api.mam
 
map_hyperexp(java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Map_hyperexpKt
Fit a two-phase Hyper-exponential renewal process as a MAP
Map_hyperexpKt - class in jline.api.mam
 
map_idc(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_idcKt
Computes the asymptotic index of dispersion (IDC) for a Markovian Arrival Process (MAP).
map_idc(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_idcKt
Computes the asymptotic index of dispersion (IDC) for a MAP stored in a MatrixCell that contains the MAP's transition matrices.
Map_idcKt - class in jline.api.mam
 
map_infgen(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_infgenKt
Computes the infinitesimal generator matrix (Q) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
map_infgen(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_infgenKt
Computes the infinitesimal generator matrix (Q) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
Map_infgenKt - class in jline.api.mam
 
map_isfeasible(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_isfeasibleKt
Checks if the provided MAP is feasible using a default tolerance.
map_isfeasible(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_isfeasibleKt
Checks if the provided MAP is feasible based on the given tolerance.
Map_isfeasibleKt - class in jline.api.mam
 
map_joint(jline.util.matrix.Matrix,jline.util.matrix.Matrix,kotlin.IntArray,kotlin.IntArray) - function in jline.api.mam.Map_jointKt
Computes the joint moments of a Markovian Arrival Process (MAP).
map_joint(jline.util.matrix.MatrixCell,kotlin.IntArray,kotlin.IntArray) - function in jline.api.mam.Map_jointKt
Computes the joint moments of a Markovian Arrival Process (MAP).
Map_jointKt - class in jline.api.mam
 
map_jointpdf_derivative(jline.util.matrix.Matrix,jline.util.matrix.Matrix,kotlin.IntArray) - function in jline.api.mam.Map_jointpdf_derivativeKt
Compute partial derivative at 0 of a MAP's joint PDF
map_jointpdf_derivative(jline.util.matrix.MatrixCell,kotlin.IntArray) - function in jline.api.mam.Map_jointpdf_derivativeKt
Compute partial derivative at 0 of a MAP's joint PDFBased on: A.
Map_jointpdf_derivativeKt - class in jline.api.mam
 
map_kpc(java.lang.Object,kotlin.Array) - function in jline.api.mam.Map_kpcKt
Kronecker product composition of MAPs.
map_kpc(kotlin.Array,kotlin.Array) - function in jline.api.mam.Map_kpcKt
Convenience function for composing exactly two MAPs.
map_kpc(java.util.List) - function in jline.api.mam.Map_kpcKt
Convenience function for composing a list of MAPs.
Map_kpcKt - class in jline.api.mam
 
map_kurt(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_kurtKt
Computes the kurtosis of the inter-arrival times in a Markovian Arrival Process (MAP).
Map_kurtKt - class in jline.api.mam
 
map_lambda(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_lambdaKt
Computes the arrival rate (lambda) of a Markovian Arrival Process (MAP).
map_lambda(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_lambdaKt
Computes the arrival rate (lambda) of a Markovian Arrival Process (MAP) using matrices stored in a MatrixCell.
Map_lambdaKt - class in jline.api.mam
 
map_largemap() - function in jline.api.mam.Map_largemapKt
Returns the maximum size considered for large MAPs.
Map_largemapKt - class in jline.api.mam
 
map_mark(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Map_markKt
Creates a Marked Markovian Arrival Process (MMAP) by marking a given Markovian Arrival Process (MAP) with additional phases based on specified marking probabilities.
Map_markKt - class in jline.api.mam
 
map_max(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_maxKt
Computes the MAP that represents the maximum of two independent MAPs.
Map_maxKt - class in jline.api.mam
 
map_mean(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_meanKt
Computes the mean inter-arrival time of a Markovian Arrival Process (MAP).
map_mean(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_meanKt
Computes the mean inter-arrival time of a Markovian Arrival Process (MAP) using matrices stored in a MatrixCell.
Map_meanKt - class in jline.api.mam
 
map_mixture(kotlin.DoubleArray,kotlin.Array) - function in jline.api.mam.Map_mixtureKt
Creates a probabilistic mixture of Markovian Arrival Processes (MAPs).
Map_mixtureKt - class in jline.api.mam
 
map_moment(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Map_momentKt
Computes the raw moments of the inter-arrival times of a Markovian Arrival Process (MAP).
map_moment(jline.util.matrix.MatrixCell,java.lang.Integer) - function in jline.api.mam.Map_momentKt
Computes the raw moments of the inter-arrival times of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
Map_momentKt - class in jline.api.mam
 
map_normalize(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_normalizeKt
Sanitizes the (D0, D1) matrices of a Markovian Arrival Process (MAP) by ensuring all elements are non-negative and adjusting diagonal elements.
map_normalize(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_normalizeKt
Sanitizes the (D0, D1) matrices of a Markovian Arrival Process (MAP) stored in a MatrixCell.
Map_normalizeKt - class in jline.api.mam
 
map_pdf(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.api.mam.Map_pdfKt
Computes the probability density function (PDF) of a MAP at a single time point.
map_pdf(jline.util.matrix.Matrix,jline.util.matrix.Matrix,kotlin.DoubleArray) - function in jline.api.mam.Map_pdfKt
Computes the probability density function (PDF) of a MAP at specified time points.
map_pdf(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_pdfKt
Computes the probability density function (PDF) of a MAP at a single time point.
map_pdf(jline.util.matrix.MatrixCell,kotlin.DoubleArray) - function in jline.api.mam.Map_pdfKt
Computes the probability density function (PDF) of a MAP at specified time points.
Map_pdfKt - class in jline.api.mam
 
map_pie(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_pieKt
Computes the steady-state probability vector of the embedded Discrete Time Markov Chain (DTMC) associated with a Markovian Arrival Process (MAP).
map_pie(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_pieKt
Computes the steady-state probability vector of the embedded DTMC of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
Map_pieKt - class in jline.api.mam
 
map_piq(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_piqKt
Computes the steady-state vector (pi) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
map_piq(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_piqKt
Computes the steady-state vector (pi) of the Continuous-Time Markov Chain (CTMC) underlying a Markovian Arrival Process (MAP).
Map_piqKt - class in jline.api.mam
 
map_pntiter(kotlin.Array,java.lang.Integer,java.lang.Double,java.lang.Integer) - function in jline.api.mam.Map_pntiterKt
Probability of having exactly na arrivals within time interval t using iterative method.
Map_pntiterKt - class in jline.api.mam
 
map_pntquad(kotlin.Array,java.lang.Integer,java.lang.Double) - function in jline.api.mam.Map_pntquadKt
Compute MAP point process probabilities using ODE quadrature method.
Map_pntquadKt - class in jline.api.mam
 
map_prob(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_probKt
Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
map_prob(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_probKt
Computes the equilibrium distribution of the underlying continuous-time Markov chain for a MAP.
Map_probKt - class in jline.api.mam
 
map_rand() - function in jline.api.mam.Map_randKt
Generates a random Markovian Arrival Process (MAP) with 2 states.
map_rand(java.lang.Integer) - function in jline.api.mam.Map_randKt
Generates a random Markovian Arrival Process (MAP) with K states.
Map_randKt - class in jline.api.mam
 
map_randn() - function in jline.api.mam.Map_randnKt
Generates a random Markovian Arrival Process (MAP) with 2 states using normal distribution with mean 1 and standard deviation 2.
map_randn(java.lang.Integer,java.lang.Double,java.lang.Double) - function in jline.api.mam.Map_randnKt
Generates a random Markovian Arrival Process (MAP) with K states using normal distribution.
Map_randnKt - class in jline.api.mam
 
map_renewal(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_renewalKt
Creates a renewal MAP by removing all correlations from the input MAP.
map_renewal(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_renewalKt
Creates a renewal MAP by removing all correlations from the input MAP.
Map_renewalKt - class in jline.api.mam
 
map_sample(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Long,java.util.Random) - function in jline.api.mam.Map_sampleKt
Generates samples of inter-arrival times from a MAP using a specified number of samples and a random generator.
map_sample(jline.util.matrix.MatrixCell,java.lang.Long,java.util.Random) - function in jline.api.mam.Map_sampleKt
Generates samples of inter-arrival times from a MAP using a specified number of samples and a random generator.
Map_sampleKt - class in jline.api.mam
 
map_scale(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.api.mam.Map_scaleKt
Rescales the mean inter-arrival time of a Markovian Arrival Process (MAP) to a specified new mean.
map_scale(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_scaleKt
Rescales the mean inter-arrival time of a MAP stored in a MatrixCell that contains the MAP's transition matrices.
Map_scaleKt - class in jline.api.mam
 
map_scv(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_scvKt
Computes the squared coefficient of variation (SCV) of the inter-arrival times of a Markovian Arrival Process (MAP).
map_scv(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_scvKt
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.
Map_scvKt - class in jline.api.mam
 
map_skew(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_skewKt
Computes the skewness of the inter-arrival times for a MAP.
map_skew(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_skewKt
Computes the skewness of the inter-arrival times for a MAP using a MatrixCell.
Map_skewKt - class in jline.api.mam
 
map_stochcomp(jline.util.matrix.Matrix,jline.util.matrix.Matrix,kotlin.IntArray) - function in jline.api.mam.Map_stochcompKt
Performs stochastic complementation on a MAP by eliminating specified states.
map_stochcomp(jline.util.matrix.MatrixCell,kotlin.IntArray) - function in jline.api.mam.Map_stochcompKt
Performs stochastic complementation on a MAP by eliminating specified states.
Map_stochcompKt - class in jline.api.mam
 
map_sum(jline.util.matrix.MatrixCell,java.lang.Integer) - function in jline.api.mam.Map_sumKt
Computes the Markovian Arrival Process (MAP) representing the sum of n identical MAPs.
map_sumind(kotlin.Array) - function in jline.api.mam.Map_sumindKt
Computes the Markovian Arrival Process (MAP) representing the sum of n independent MAPs.
Map_sumindKt - class in jline.api.mam
 
Map_sumKt - class in jline.api.mam
 
map_super(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_superKt
Creates a superposition of two Markovian Arrival Processes (MAPs) to form a new MAP.
Map_superKt - class in jline.api.mam
 
map_timereverse(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_timereverseKt
Computes the time-reversed MAP of a given MAP.
Map_timereverseKt - class in jline.api.mam
 
map_var(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_varKt
Computes the variance of the inter-arrival times for a MAP.
map_var(jline.util.matrix.MatrixCell) - function in jline.api.mam.Map_varKt
Computes the variance of the inter-arrival times for a MAP using a MatrixCell.
map_varcount(jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Map_varcountKt
Computes the variance of the counts in a MAP over multiple time periods.
map_varcount(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.api.mam.Map_varcountKt
Computes the variance of the counts in a MAP over a time period t.
map_varcount(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Map_varcountKt
Computes the variance of the counts in a MAP over multiple time periods using a MatrixCell.
map_varcount(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Map_varcountKt
Computes the variance of the counts in a MAP over a time period t using a MatrixCell.
Map_varcountKt - class in jline.api.mam
 
Map_varKt - class in jline.api.mam
 
MapAcfAlgo - class in jline.api.mam
MAP autocorrelation function algorithms
MapAcfcAlgo - class in jline.api.mam
MAP autocorrelation function coefficients algorithms
MapBlockAlgo - class in jline.api.mam
MAP block matrix construction algorithms
MAPCatalog - class in jline.lib.kpctoolbox
Complete catalog of MAP (Markovian Arrival Process) models migrated from MATLAB Location: /home/gcasale/code/matlab/maps/ This class provides static methods to create all MAP and MMPP2 models from the maps directory including those from .mat files and .m function files.
MapCcdfDerivativeAlgo - class in jline.api.mam
MAP complementary CDF derivative algorithms
MapCdf - class in jline.api.mam
MAP cumulative distribution function algorithms
MapCheckfeasibleAlgo - class in jline.api.mam
MAP checkfeasible algorithms
MapCountMeanAlgo - class in jline.api.mam
MAP counting process mean algorithms
MapCountMoment - class in jline.api.mam
MAP count moment algorithms
MapCountVar - class in jline.api.mam
MAP count var algorithms
MAPDcOptions - class in jline.lib.qmam
Options for MAP/D/c queue analysis
MAPDcResult - class in jline.lib.qmam
Result of MAP/D/c queue analysis
mape(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.bench.BenchmarkUtils
Calculate Mean Absolute Percentage Error (MAPE) Wrapper for Utils.
mape(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.util.Utils
Return mean absolute percentage error of approx with respect to exact
MapEmbeddedAlgo - class in jline.api.mam
MAP embedded algorithms
MapErlangAlgo - class in jline.api.mam
MAP erlang algorithms
mapeWithNanMean(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.util.Utils
Polymorphic version that returns both MAPE and nanMean.
MapExponentialAlgo - class in jline.api.mam
MAP exponential algorithms
MapFeasblockAlgo - class in jline.api.mam
MAP feasblock algorithms
MapFeastolAlgo - class in jline.api.mam
MAP feastol algorithms
MapGamma2 - class in jline.api.mam
MAP gamma2 algorithms
MapGammaAlgo - class in jline.api.mam
MAP gamma algorithms
maph2m_fit(java.lang.Double,java.lang.Double,java.lang.Double,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Maph2m_fitKt
Computes the second-order MAPHm fitting the given ordinary moments (of order up to three), the class probabilities (always fitted exactly) and the backward moments.
maph2m_fit_mmap(jline.util.matrix.MatrixCell) - function in jline.api.mam.Maph2m_fit_mmapKt
Fits an MMAPm with a second-order MAPHm that matches the class probabilities (always fitted exactly) and the backward moments.
Maph2m_fit_mmapKt - class in jline.api.mam
 
maph2m_fit_multiclass(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Maph2m_fitKt
Fits MAPH(2,m) for multiple classes given underlying APH(2), class probabilities, and backward moments.
maph2m_fit_multiclass(java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,kotlin.DoubleArray) - function in jline.api.mam.Maph2m_fit_multiclassKt
Fits a multi-class MAPH(2,m) model to given multi-class characteristics.
Maph2m_fit_multiclassKt - class in jline.api.mam
 
maph2m_fit_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Maph2m_fit_traceKt
Fits a multi-class MAPH(2,m) model to trace data with class labels.
maph2m_fit_trace_timestamps(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Maph2m_fit_traceKt
Fits a multi-class MAPH(2,m) model to trace data with arrival time stamps and class labels.
Maph2m_fit_traceKt - class in jline.api.mam
 
maph2m_fitc_approx(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.Maph2m_fitc_approxKt
Fits a second-order Marked MMPP using approximate count-based characteristics.
Maph2m_fitc_approxKt - class in jline.api.mam
 
maph2m_fitc_exact(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.Maph2m_fitc_theoreticalKt
Exact fitting method using all available characteristics
maph2m_fitc_theoretical(jline.util.matrix.MatrixCell,java.lang.String) - function in jline.api.mam.Maph2m_fitc_theoreticalKt
Fits the theoretical characteristics of a MMAP(n,m) with a M3PP(2,m).
Maph2m_fitc_theoreticalKt - class in jline.api.mam
 
Maph2m_fitKt - class in jline.api.mam
 
Maph2mFitAlgo - class in jline.api.mam
MAPH 2m fit algorithms
Maph2mFitCountApproxAlgo - class in jline.api.mam
MAPH 2m fit count approx algorithms
Maph2mFitCountTheoreticalAlgo - class in jline.api.mam
MAPH 2m fit count theoretical algorithms
Maph2mFitMmapAlgo - class in jline.api.mam
MAPH 2m fit mmap algorithms
Maph2mFitMulticlass - class in jline.api.mam
MAPH 2m fit multiclass algorithms
Maph2mFitTraceAlgo - class in jline.api.mam
MAPH 2m fit trace algorithms
maph2ObjectiveFunction(kotlin.DoubleArray,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Double) - function in jline.api.mam.Maph2m_fitc_approxKt
Objective function for MAPH(2) parameter optimization
MapHyperexpAlgo - class in jline.api.mam
MAP hyperexp algorithms
MapIdcAlgo - class in jline.api.mam
MAP idc algorithms
MapInfgenAlgo - class in jline.api.mam
MAP infgen algorithms
MapIsfeasibleAlgo - class in jline.api.mam
MAP isfeasible algorithms
MapJointAlgo - class in jline.api.mam
MAP joint algorithms
MapJointpdfDerivativeAlgo - class in jline.api.mam
MAP jointpdf derivative algorithms
MapKpcAlgo - class in jline.api.mam
MAP kpc algorithms
MapKurtAlgo - class in jline.api.mam
MAP kurt algorithms
MapLambda - class in jline.api.mam
MAP arrival rate computation algorithms.
MapLargemapAlgo - class in jline.api.mam
MAP largemap algorithms
MAPM1PSCdfRespT - class in jline.api.map
MAP/M/1-PS Sojourn Time DistributionComputes the complementary distribution function of sojourn time in a MAP/M/1 processor-sharing queue using the algorithm from:Masuyama, H.
MAPMAP1Options - class in jline.lib.qmam
Options for MAP/MAP/1 queue analysis
MAPMAP1Result - class in jline.lib.qmam
Result of MAP/MAP/1 queue analysis
MapMarkAlgo - class in jline.api.mam
MAP mark algorithms
MapMaxAlgo - class in jline.api.mam
MAP max algorithms
MAPMcOptions - class in jline.lib.qmam
Options for MAP/M/c queue analysis
MAPMcResult - class in jline.lib.qmam
Result of MAP/M/c queue analysis
MapMean - class in jline.api.mam
MAP mean inter-arrival time computation algorithms.
MapMixture - class in jline.api.mam
MAP mixture algorithms
MapMoment - class in jline.api.mam
MAP moment algorithms
MapNormalizeAlgo - class in jline.api.mam
MAP normalize algorithms
MapPdfAlgo - class in jline.api.mam
MAP pdf algorithms
MapPieAlgo - class in jline.api.mam
MAP pie algorithms
MapPiqAlgo - class in jline.api.mam
MAP piq algorithms
MapPntiterAlgo - class in jline.api.mam
MAP pntiter algorithms
MapPntquad - class in jline.api.mam
MAP pntquad algorithms
MapProbAlgo - class in jline.api.mam
MAP prob algorithms
Mapqn_bnd_lr - class in jline.api.mapqn
Implementation of bnd_linearreduction_new.
Mapqn_bnd_lr_mva - class in jline.api.mapqn
Implementation of bnd_mvaversion.
Mapqn_bnd_lr_mvaKt - class in jline.api.mapqn
 
Mapqn_bnd_lr_pf - class in jline.api.mapqn
Implementation of bnd_linearreduction_pf.
Mapqn_bnd_lr_pf.PFParameters - class in jline.api.mapqn.Mapqn_bnd_lr_pf
Parameters for the Product Form linear reduction model
Mapqn_bnd_lr_pfKt - class in jline.api.mapqn
 
Mapqn_bnd_qr - class in jline.api.mapqn
Implementation of bnd_quadraticreduction.
Mapqn_bnd_qr_delay - class in jline.api.mapqn
Implementation of bnd_quadraticreduction_delay.
Mapqn_bnd_qr_delay.QuadraticDelayParameters - class in jline.api.mapqn.Mapqn_bnd_qr_delay
Parameters for the quadratic reduction delay model
Mapqn_bnd_qr_delayKt - class in jline.api.mapqn
 
Mapqn_bnd_qr_ld - class in jline.api.mapqn
Implementation of bnd_quadraticreduction_ld.
Mapqn_bnd_qr_ld.QuadraticLDParameters - class in jline.api.mapqn.Mapqn_bnd_qr_ld
Parameters for the quadratic reduction load-dependent model
Mapqn_lpmodel - class in jline.api.mapqn
Base class for representing MAPQN Linear Programming models
Mapqn_lpmodel.LinearConstraintBuilder - class in jline.api.mapqn.Mapqn_lpmodel
Helper class for building linear constraints
Mapqn_parameters - class in jline.api.mapqn
Base class for MAPQN model parameters
Mapqn_parameters_factory - class in jline.api.mapqn
Factory class for creating Mapqn_parameters from NetworkStruct.
Mapqn_qr_bounds_bas - class in jline.api.mapqn
Implementation of qrf_bas.
Mapqn_qr_bounds_bas_parameters - class in jline.api.mapqn
Parameters for QR Bounds BAS (Blocking After Service) model
Mapqn_qr_bounds_rsrd - class in jline.api.mapqn
Implementation of qrf_rsrd.
Mapqn_qr_bounds_rsrd_parameters - class in jline.api.mapqn
Parameters for QR Bounds RSRD (Repetitive Service Random Destination) model
Mapqn_solution - class in jline.api.mapqn
Solution container for MAPQN linear programs
MapRandAlgo - class in jline.api.mam
MAP rand algorithms
MapRandnAlgo - class in jline.api.mam
MAP randn algorithms
MapRenewal - class in jline.api.mam
MAP renewal algorithms
MAPRepresentation - class in jline.lib.butools.map
Result class for RandomMAP.
MapSampleAlgo - class in jline.api.mam
MAP sample algorithms
MapScaleAlgo - class in jline.api.mam
MAP scale algorithms
MapScvAlgo - class in jline.api.mam
MAP scv algorithms
MapSkewAlgo - class in jline.api.mam
MAP skew algorithms
MapStochcompAlgo - class in jline.api.mam
MAP stochcomp algorithms
MapSumAlgo - class in jline.api.mam
MAP sum algorithms
MapSumindAlgo - class in jline.api.mam
MAP sumind algorithms
MapSuperAlgo - class in jline.api.mam
MAP super algorithms
MapTimereverseAlgo - class in jline.api.mam
MAP timereverse algorithms
MapVar - class in jline.api.mam
MAP variance computation algorithms.
MapVarcountAlgo - class in jline.api.mam
MAP varcount algorithms
marginal(jline.lib.perm.PermSolver,kotlin.IntArray,java.lang.Boolean) - function in jline.lib.perm.NetworkNoThink
Compute marginal probability of a state using specified solver.
marginal(jline.lib.perm.PermSolver,kotlin.IntArray,java.lang.Boolean) - function in jline.lib.perm.NetworkThink
Compute marginal probability including think time effects.
marginalDistributionFromDMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.lib.butools.dmap.MarginalDistributionFromDMAPKt
Returns the discrete phase type distributed marginal distribution of a discrete Markovian arrival process.
MarginalDistributionFromDMAPKt - class in jline.lib.butools.dmap
 
marginalDistributionFromDMMAP(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.lib.butools.dmap.MarginalDistributionFromDMMAPKt
Returns the discrete phase type distributed marginal distribution of a discrete marked Markovian arrival process.
marginalDistributionFromDMMAP(kotlin.Array,java.lang.Double) - function in jline.lib.butools.dmap.MarginalDistributionFromDMMAPKt
Overload for Array<Matrix>.
MarginalDistributionFromDMMAPKt - class in jline.lib.butools.dmap
 
marginalDistributionFromDMRAP(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.lib.butools.dmap.MarginalDistributionFromDMRAPKt
Returns the matrix geometrically distributed marginal distribution of a discrete marked rational arrival process.
marginalDistributionFromDMRAP(kotlin.Array,java.lang.Double) - function in jline.lib.butools.dmap.MarginalDistributionFromDMRAPKt
Overload for Array<Matrix>.
MarginalDistributionFromDMRAPKt - class in jline.lib.butools.dmap
 
marginalDistributionFromDRAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.lib.butools.dmap.MarginalDistributionFromDRAPKt
Returns the matrix geometrically distributed marginal distribution of a discrete rational arrival process.
MarginalDistributionFromDRAPKt - class in jline.lib.butools.dmap
 
marginalDistributionFromMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.butools.map.MarginalDistributionFromMAPKt
Returns the phase type distributed marginal distribution of a Markovian arrival process.
MarginalDistributionFromMAPKt - class in jline.lib.butools.map
 
marginalDistributionFromRAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.butools.map.MarginalDistributionFromMAPKt
Returns the matrix exponential distributed marginal distribution of a rational arrival process.
marginalMomentsFromDMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer,java.lang.Double) - function in jline.lib.butools.dmap.MarginalMomentsFromDMAPKt
Returns the moments of the marginal distribution of a discrete Markovian arrival process.
marginalMomentsFromDMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.dmap.MarginalMomentsFromDMAPKt
Returns the moments of the marginal distribution of a discrete Markovian arrival process.
marginalMomentsFromDMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.butools.dmap.MarginalMomentsFromDMAPKt
Returns the moments of the marginal distribution of a discrete Markovian arrival process.
MarginalMomentsFromDMAPKt - class in jline.lib.butools.dmap
 
marginalMomentsFromDMMAP(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Double) - function in jline.lib.butools.dmap.MarginalMomentsFromDMMAPKt
Returns the moments of the marginal distribution of a discrete marked Markovian arrival process.
marginalMomentsFromDMMAP(kotlin.Array,java.lang.Integer,java.lang.Double) - function in jline.lib.butools.dmap.MarginalMomentsFromDMMAPKt
Overload for Array<Matrix>.
MarginalMomentsFromDMMAPKt - class in jline.lib.butools.dmap
 
marginalMomentsFromDMRAP(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Double) - function in jline.lib.butools.dmap.MarginalMomentsFromDMRAPKt
Returns the moments of the marginal distribution of a discrete marked rational arrival process.
marginalMomentsFromDMRAP(kotlin.Array,java.lang.Integer,java.lang.Double) - function in jline.lib.butools.dmap.MarginalMomentsFromDMRAPKt
Overload for Array<Matrix>.
MarginalMomentsFromDMRAPKt - class in jline.lib.butools.dmap
 
marginalMomentsFromDRAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer,java.lang.Double) - function in jline.lib.butools.dmap.MarginalMomentsFromDRAPKt
Returns the moments of the marginal distribution of a discrete rational arrival process.
MarginalMomentsFromDRAPKt - class in jline.lib.butools.dmap
 
marginalMomentsFromMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.map.MarginalMomentsFromMAPKt
Returns the moments of the marginal distribution of a Markovian arrival process.
marginalMomentsFromMAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.butools.map.MarginalMomentsFromMAPKt
Returns the moments of the marginal distribution of a Markovian arrival process.
MarginalMomentsFromMAPKt - class in jline.lib.butools.map
 
marginalMomentsFromRAP(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.map.MarginalMomentsFromMAPKt
Returns the moments of the marginal distribution of a rational arrival process.
marginalMomentsFromTrace(kotlin.DoubleArray,java.lang.Integer) - function in jline.lib.butools.trace.MarginalMomentsFromTraceKt
Returns the marginal moments of a trace.
MarginalMomentsFromTraceKt - class in jline.lib.butools.trace
 
marginalMomentsFromWeightedTrace(kotlin.DoubleArray,kotlin.DoubleArray,java.lang.Integer) - function in jline.lib.butools.trace.MarginalMomentsFromTraceKt
Returns the marginal moments of a weighted trace.
Marked - class in jline.lang.processes
An abstract class for marked point processes
MarkedMAP - class in jline.lang.processes
A Marked Markovian Arrival Process
MarkedMarkovProcess - class in jline.lang.processes
A class for continuous time Markov chain where transitions are labeled
MarkedMMPP - class in jline.lang.processes
A Marked Markov-Modulated Poisson Process (M3PP)
MarkovChain - class in jline.lang.processes
A class for a discrete time Markov chain
Markovian - class in jline.lang.processes
An abstract class for a Markovian distribution
MarkovianRepresentation - class in jline.lib.butools.reptrans
Result class for ExtendToMarkovian.
MarkovModulated - class in jline.lang.processes
An abstract class for a Markov-modulated point-process
MarkovProcess - class in jline.lang.processes
A class for a continuous time Markov chain
matchRow(java.util.List,kotlin.Array) - function in jline.util.Maths
Finds the index of a matching row in a list.
matchrow(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.util.matrix.Matrix
Returns the index of the row in the matrix that exactly matches the given row vector.
MatFileUtils - class in jline.util
Utility class for saving matrices and workspaces to MATLAB .mat files using the MFL (MATLAB File Library) for Java.
Maths - class in jline.util
Mathematical functions and utilities.
Maths.laplaceApproxComplexReturn - class in jline.util.Maths
 
Maths.laplaceApproxReturn - class in jline.util.Maths
 
Maths.simplexQuadResult - class in jline.util.Maths
 
Matrix - class in jline.util.matrix
A sparse matrix data structure supporting linear algebra functions similar to those available in MATLAB.
matrixAddVector(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.util.matrix.Matrix
Adds a vector to each row or column of the matrix, depending on the vector's orientation.
MatrixCell - class in jline.util.matrix
An ordered collection of Matrix objects that provides indexing and manipulation operations.
MatrixEquation - class in jline.util.matrix
A wrapper class that extends EJML's Equation functionality to work seamlessly with jline.util.matrix.Matrix objects.
matrixExp(jline.util.matrix.Matrix) - function in jline.util.Maths
Adapted from jblas and IHMC Original documentation: Calculate matrix exponential of a square matrix.
MatrixMethodAnalyzer - class in jline.solvers.fluid.analyzers
 
MatrixMethodODE - class in jline.solvers.fluid.handlers
 
max(double,double) - function in jline.util.Maths
Returns the max of two numbers.
maxAbsDiff(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.util.matrix.Matrix
Computes the maximum relative absolute difference between corresponding elements of two matrices: max(abs((a - b) / b)).
maxErrorOnSum(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.bench.BenchmarkUtils
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)
maxpos(kotlin.DoubleArray) - function in jline.lib.kpctoolbox.basic.BasicUtilsKt
Finds the position of the maximum value in a vector.
maxpos(kotlin.DoubleArray,java.lang.Integer) - function in jline.lib.kpctoolbox.basic.BasicUtilsKt
Finds the positions of the n largest values in a vector.
maxpos(jline.util.matrix.Matrix) - function in jline.util.Maths
Returns the position of the maximum value in a vector.
maxpos(jline.util.matrix.Matrix,int) - function in jline.util.Maths
Returns the positions of the n largest values in a vector.
maxStates(int) - function in jline.solvers.mam.MAMOptions
 
MC - enum entry in jline.bench.fj.BenchFJ_Template.FJConfig
 
MC2 - enum entry in jline.bench.fj.BenchFJ_Template.FJConfig
 
MC3 - enum entry in jline.bench.fj.BenchFJ_Template.FJConfig
 
MC4 - enum entry in jline.bench.fj.BenchFJ_Template.FJConfig
 
ME - enum entry in jline.lang.constant.ProcessType
 
ME - class in jline.lang.processes
A Matrix Exponential (ME) distribution.
me_mean(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Me_meanKt
Computes the mean of a Matrix Exponential (ME) distribution.
me_mean(jline.util.matrix.MatrixCell) - function in jline.api.mam.Me_meanKt
Computes the mean of a Matrix Exponential (ME) distribution using matrices stored in a MatrixCell.
Me_meanKt - class in jline.api.mam
 
me_oqn(java.lang.Integer,java.lang.Integer,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix,kotlin.Array,jline.api.nc.MeOqnOptions) - function in jline.api.nc.Me_oqnKt
Maximum Entropy algorithm for Open Queueing Networks.
Me_oqnKt - class in jline.api.nc
 
me_pie(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Me_pieKt
Computes the stationary initial probability for an ME/RAP distribution.
me_pie(jline.util.matrix.MatrixCell) - function in jline.api.mam.Me_pieKt
Computes the stationary initial probability for an ME/RAP distribution using matrices stored in a MatrixCell.
Me_pieKt - class in jline.api.mam
 
me_sample(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Long,java.util.Random) - function in jline.api.mam.Me_sampleKt
Generates random samples from a Matrix Exponential (ME) distribution using inverse CDF interpolation.
me_sample(jline.util.matrix.MatrixCell,java.lang.Long,java.util.Random) - function in jline.api.mam.Me_sampleKt
Generates random samples from an ME distribution using matrices stored in a MatrixCell.
Me_sampleKt - class in jline.api.mam
 
me_scv(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Me_scvKt
Computes the squared coefficient of variation (SCV) of a Matrix Exponential (ME) distribution.
me_scv(jline.util.matrix.MatrixCell) - function in jline.api.mam.Me_scvKt
Computes the squared coefficient of variation (SCV) of an ME distribution using matrices stored in a MatrixCell.
Me_scvKt - class in jline.api.mam
 
me_var(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Me_varKt
Computes the variance of a Matrix Exponential (ME) distribution.
me_var(jline.util.matrix.MatrixCell) - function in jline.api.mam.Me_varKt
Computes the variance of a Matrix Exponential (ME) distribution using matrices stored in a MatrixCell.
Me_varKt - class in jline.api.mam
 
mean() - function in jline.lang.processes.Coxian
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Coxian
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Det
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Distribution
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Distribution
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Erlang
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Exp
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Gamma
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.HyperExp
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Lognormal
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Markovian
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Markovian
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.PH
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Pareto
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Uniform
Kotlin-style property alias for getMean()
mean() - function in jline.lang.processes.Weibull
Kotlin-style property alias for getMean()
meanCol() - function in jline.util.matrix.Matrix
Computes the mean of each column.
meanRow() - function in jline.util.matrix.Matrix
Computes the mean of each row.
meFromMoments(kotlin.DoubleArray) - function in jline.lib.butools.ph.MEFromMomentsKt
Creates a matrix-exponential distribution that has the same moments as given.
MEFromMomentsKt - class in jline.lib.butools.ph
 
MeMean - class in jline.api.mam
ME mean computation algorithms documentation marker for Dokka.
meOpen() - function in jline.solvers.nc.SolverNC
Maximum Entropy algorithm for Open Queueing Networks.
meOpen() - function in jline.solvers.nc.SolverNC
Maximum Entropy algorithm for Open Queueing Networks.
meOpen(jline.api.nc.MeOqnOptions) - function in jline.solvers.nc.SolverNC
Maximum Entropy algorithm for Open Queueing Networks with custom options.
meOpen(jline.api.nc.MeOqnOptions) - function in jline.solvers.nc.SolverNC
Maximum Entropy algorithm for Open Queueing Networks with custom options.
MeOqn - class in jline.api.nc
ME OQN algorithms documentation marker for Dokka.
MeOqnOptions - class in jline.api.nc
Options for the ME OQN algorithm.
MeOqnResult - class in jline.api.nc
Result of the ME OQN algorithm.
MePie - class in jline.api.mam
ME initial probability computation algorithms documentation marker for Dokka.
MERepresentation - class in jline.lib.butools.ph
Result class for MEFromMoments containing both alpha and A.
merge(java.util.List) - function in jline.lang.Ensemble
Creates a union Network from a list of Networks.
merge(java.util.List) - function in jline.lang.Ensemble
Creates a union Network from a list of Networks.
merge(jline.lang.Ensemble) - function in jline.lang.Ensemble
Creates a union Network from all Networks in an ensemble.
merge(jline.lang.Ensemble) - function in jline.lang.Ensemble
Creates a union Network from all Networks in an ensemble.
merge(int,int) - function in jline.lang.processes.GMM
Merges two components into one using moment matching.
MeSample - class in jline.api.mam
ME sampling algorithms documentation marker for Dokka.
MeScv - class in jline.api.mam
ME SCV computation algorithms documentation marker for Dokka.
method(java.lang.String) - function in jline.solvers.SolverOptions
Sets the solution method/algorithm (builder pattern).
method(java.lang.String) - function in jline.solvers.SolverOptions
Sets the solution method/algorithm (builder pattern).
MethodStepHandler - class in jline.solvers.fluid.handlers
 
Metric - class in jline.lang
Constants for specifying a Metric
MetricsResult - class in jline.solvers.mam.handlers
 
MetricType - class in jline.lang.constant
Constants for specifying a type of metric
MeVar - class in jline.api.mam
ME variance computation algorithms documentation marker for Dokka.
mfilename(java.lang.Object) - function in jline.io.InputOutputKt
 
mg1_cr(jline.util.matrix.Matrix,jline.lib.smc.MG1CROptions) - function in jline.lib.smc.MG1_piKt
Computes the G matrix using Cyclic Reduction for M/G/1-type chains.
mg1_eg(jline.util.matrix.Matrix,java.lang.Boolean) - function in jline.lib.smc.MG1_EGKt
Determines G directly if rank(A0)=1 for M/G/1-type Markov chains.
MG1_EGKt - class in jline.lib.smc
 
mg1_fi(jline.util.matrix.Matrix,jline.lib.smc.MG1FIOptions) - function in jline.lib.smc.MG1_FIKt
Functional Iterations for M/G/1-Type Markov Chains.
MG1_FIKt - class in jline.lib.smc
 
mg1_pi(jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.lib.smc.MG1PiOptions) - function in jline.lib.smc.MG1_piKt
Computes the stationary distribution of an M/G/1-type Markov chain.
MG1_piKt - class in jline.lib.smc
 
mg1_shifts(jline.util.matrix.Matrix,java.lang.String) - function in jline.lib.smc.MG1_ShiftsKt
Applies the shift technique to an M/G/1-type block matrix.
MG1_ShiftsKt - class in jline.lib.smc
 
MG1CROptions - class in jline.lib.smc
Options for MG1_CR solver
MG1FIOptions - class in jline.lib.smc
Options for MG1_FI solver
mg1FundamentalMatrix(java.util.List,java.lang.Double,java.lang.Integer,jline.lib.butools.mam.MG1Method) - function in jline.lib.butools.mam.MG1FundamentalMatrixKt
Returns matrix G corresponding to the M/G/1 type Markov chain defined by matrices A.
MG1FundamentalMatrixKt - class in jline.lib.butools.mam
 
MG1Method - class in jline.lib.butools.mam
Method for solving M/G/1 type matrix equation.
MG1PiOptions - class in jline.lib.smc
Options for MG1_pi solver
MG1ShiftResult - class in jline.lib.smc
Result of MG1 shift transformation
mgFromMoments(kotlin.DoubleArray) - function in jline.lib.butools.dph.MGFromMomentsKt
Creates a matrix-geometric distribution that has the same moments as given.
MGFromMomentsKt - class in jline.lib.butools.dph
 
MGRepresentation - class in jline.lib.butools.dph
Result class for MGFromMoments containing both alpha and A.
min(double,double) - function in jline.util.Maths
Returns the min of two numbers.
MINIMAL - enum entry in jline.api.sn.ValidationLevel

Minimal validation - only basic bounds checking.

  • Index bounds checking

  • NaN detection

minpos(kotlin.DoubleArray) - function in jline.lib.kpctoolbox.basic.BasicUtilsKt
Finds the position of the minimum value in a vector.
minpos(kotlin.DoubleArray,java.lang.Integer) - function in jline.lib.kpctoolbox.basic.BasicUtilsKt
Finds the positions of the n smallest values in a vector.
minpos(jline.util.matrix.Matrix) - function in jline.util.Maths
Returns the position of the minimum value in a vector.
minpos(jline.util.matrix.Matrix,int) - function in jline.util.Maths
Returns the positions of the n smallest values in a vector.
MixedExamples - class in jline.examples.java.basic
Mixed queueing network examples mirroring the Kotlin notebooks in mixedQN.
MixedModel - class in jline.examples.java.basic
Examples of mixed queueing networks
mixture(jline.lang.processes.GMM,jline.lang.processes.GMM,double,double) - function in jline.lang.processes.GMM
Creates a mixture of two GMMs with specified weights.
mm1() - function in jline.examples.java.advanced.FCRegionModel
Simple M/M/1 without FCR (for comparison).
mm1k() - function in jline.examples.java.advanced.FCRegionModel
M/M/1/K using queue capacity (K=2, for comparison).
mmap_backward_moment(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Mmap_backward_momentKt
Computes the backward moments of an MMAP for specified orders with normalization.
Mmap_backward_momentKt - class in jline.api.mam
 
Mmap_compress - class in jline.api.mam
Compresses an MMAP using various approximation methods.
mmap_compress(kotlin.Array,java.lang.String) - function in jline.api.mam.Mmap_compress.Companion
 
mmap_compress(kotlin.Array) - function in jline.api.mam.Mmap_compress.Companion
 
mmap_count_idc(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_count_idcKt
Computes the index of dispersion for counts (IDC) for a Markovian Arrival Process with marked arrivals (MMAP) over a time period.
Mmap_count_idcKt - class in jline.api.mam
 
mmap_count_lambda(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_count_lambdaKt
Computes the arrival rate vector of the counting process for the given Marked MAP (MMAP).
Mmap_count_lambdaKt - class in jline.api.mam
 
mmap_count_mcov(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_count_mcovKt
Computes the count covariance between each pair of classes at a given time scale.
mmap_count_mcov(kotlin.Array,java.lang.Double) - function in jline.api.mam.Mmap_count_mcovKt
Computes the count covariance between each pair of classes at a given time scale.
Mmap_count_mcovKt - class in jline.api.mam
 
mmap_count_mean(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_count_meanKt
Computes the mean count vector of events of different types in a Markovian Arrival Process with marked arrivals (MMAP) over a time period.
mmap_count_mean_class(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Double) - function in jline.api.mam.Maph2m_fitc_theoreticalKt
Helper functions for MMAP analysis - these would be implemented with full MMAP theory
Mmap_count_meanKt - class in jline.api.mam
 
mmap_count_var(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_count_varKt
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.
mmap_count_var_class(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Double) - function in jline.api.mam.Maph2m_fitc_theoreticalKt
 
mmap_count_var_others(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Double) - function in jline.api.mam.Maph2m_fitc_theoreticalKt
 
Mmap_count_varKt - class in jline.api.mam
 
mmap_cross_modulate(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_modulateKt
Cross-modulation between two MMAPs.
mmap_cross_moment(jline.util.matrix.MatrixCell,java.lang.Integer) - function in jline.api.mam.Mmap_cross_momentKt
Computes the k-th cross-moment matrix for a given MMAP.
Mmap_cross_momentKt - class in jline.api.mam
 
mmap_embedded(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_embeddedKt
Computes the embedded chain of an MMAP.
Mmap_embeddedKt - class in jline.api.mam
 
mmap_exponential(jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_exponentialKt
Fits a Markovian Arrival Process with marked arrivals (MMAP) with a single state based on the given arrival rates for each job class.
mmap_exponential(jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Mmap_exponentialKt
Fits an order-n Markovian Arrival Process with marked arrivals (MMAP) based on the given arrival rates for each job class.
Mmap_exponentialKt - class in jline.api.mam
 
mmap_forward_moment(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Mmap_forward_momentKt
Computes the forward moments of an MMAP for specified orders with normalization.
mmap_forward_moment(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_forward_momentKt
Computes the forward moments of an MMAP for specified orders with normalization.
Mmap_forward_momentKt - class in jline.api.mam
 
mmap_hide(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_hideKt
Hides specified types of arrivals in a Markovian Arrival Process with marked arrivals (MMAP).
Mmap_hideKt - class in jline.api.mam
 
mmap_idc(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_idcKt
Computes the asymptotic index of dispersion for counts (IDC) for a Markovian Arrival Process with marked arrivals (MMAP).
Mmap_idcKt - class in jline.api.mam
 
mmap_isfeasible(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_isfeasibleKt
Checks the feasibility of a Markovian Arrival Process with marked arrivals (MMAP).
Mmap_isfeasibleKt - class in jline.api.mam
 
mmap_issym(jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_issymKt
Checks if an MMAP is symmetric.
Mmap_issymKt - class in jline.api.mam
 
mmap_lambda(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_lambdaKt
Alias for mmap_count_lambda.
Mmap_lambdaKt - class in jline.api.mam
 
mmap_maps(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_mapsKt
Extracts K Markovian Arrival Processes (MAPs) from a given MMAP, one for each class.
Mmap_mapsKt - class in jline.api.mam
 
mmap_mark(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_markKt
Converts a Markovian Arrival Process with marked arrivals (MMAP) into a new MMAP with redefined classes based on a given probability matrix.
Mmap_markKt - class in jline.api.mam
 
mmap_max(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_maxKt
Computes the element-wise maximum of two MMAPs.
mmap_max_multiple(java.util.List) - function in jline.api.mam.Mmap_maxKt
Computes the element-wise maximum of multiple MMAPs.
Mmap_maxKt - class in jline.api.mam
 
mmap_mixture(jline.util.matrix.Matrix,java.util.Map) - function in jline.api.mam.Mmap_mixtureKt
Creates a mixture of MMAPs using the given weights (alpha) and MAPs.
mmap_mixture_fit(java.lang.Object,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_mixture_fitKt
Fits a mixture of Markovian Arrival Processes (MMAPs) to match the given cross-moments.
mmap_mixture_fit(jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_mixture_fit_traceKt
Fits a MMAP using mixture of PH distributions based on moments.
mmap_mixture_fit_mmap(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_mixture_fit_mmapKt
Fits a mixture of Markovian Arrival Processes (MMAPs) to match the given moments.
Mmap_mixture_fit_mmapKt - class in jline.api.mam
 
mmap_mixture_fit_trace(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_mixture_fit_traceKt
Fits a MMAP with m classes using a mixture of m^2 PH-distributions from Matrix inputs.
mmap_mixture_fit_trace(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Mmap_mixture_fit_traceKt
Fits a MMAP with m classes using a mixture of m^2 PH-distributions from trace data.
Mmap_mixture_fit_traceKt - class in jline.api.mam
 
Mmap_mixture_fitKt - class in jline.api.mam
 
mmap_mixture_order2(java.util.List,kotlin.DoubleArray) - function in jline.api.mam.Mmap_mixture_order2Kt
Creates a second-order MMAP mixture from a collection of MMAPs.
mmap_mixture_order2_optimal(java.util.List,kotlin.DoubleArray) - function in jline.api.mam.Mmap_mixture_order2Kt
Creates a second-order MMAP mixture with automatic weight selection.
Mmap_mixture_order2Kt - class in jline.api.mam
 
Mmap_mixtureKt - class in jline.api.mam
 
mmap_modulate(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,java.lang.Double) - function in jline.api.mam.Mmap_modulateKt
Modulates an MMAP by another MMAP, creating a compound arrival process.
mmap_modulate_time_varying(jline.util.matrix.MatrixCell,kotlin.jvm.functions.Function1,java.lang.Double,java.lang.Integer) - function in jline.api.mam.Mmap_modulateKt
Time-varying modulation of an MMAP.
Mmap_modulateKt - class in jline.api.mam
 
mmap_normalize(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_normalizeKt
Normalizes a Markovian Arrival Process with marked arrivals (MMAP) to ensure feasibility.
Mmap_normalizeKt - class in jline.api.mam
 
mmap_pc(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_pcKt
Computes the proportion of counts (PC) for each type in a Markovian Arrival Process with marked arrivals (MMAP).
Mmap_pcKt - class in jline.api.mam
 
Mmap_pie - class in jline.api.mam
Computes the steady-state probability vector for each class in an MMAP.
mmap_pie(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_pie.Companion
 
mmap_pie(kotlin.Array) - function in jline.api.mam.Mmap_pie.Companion
Overloaded version for Array<Matrix> input
mmap_rand(java.lang.Integer,java.lang.Integer) - function in jline.api.mam.Mmap_randKt
Generates a random MMAP (Marked Markovian Arrival Process) with a given order and number of classes.
Mmap_randKt - class in jline.api.mam
 
mmap_sample(jline.util.matrix.MatrixCell,java.lang.Long,java.util.Random) - function in jline.api.mam.Mmap_sampleKt
Generates samples of inter-arrival times and event types from a MMAP using a specified number of samples.
Mmap_sampleKt - class in jline.api.mam
 
mmap_scale(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix) - function in jline.api.mam.Mmap_scaleKt
Overloaded function for backward compatibility
mmap_scale(jline.util.matrix.MatrixCell,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.api.mam.Mmap_scaleKt
Changes the mean inter-arrival time of a Markovian Arrival Process with marked arrivals (MMAP).
Mmap_scaleKt - class in jline.api.mam
 
mmap_shorten(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_shortenKt
Converts an MMAP representation from M3A format to BUTools format.
Mmap_shortenKt - class in jline.api.mam
 
mmap_sigma(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_sigmaKt
Computes one-step class transition probabilities for a Marked Markovian Arrival Process (MMAP).
mmap_sigma(kotlin.Array) - function in jline.api.mam.Mmap_sigmaKt
Computes one-step class transition probabilities for a Marked Markovian Arrival Process (MMAP).
mmap_sigma2(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_sigma2Kt
Computes two-step class transition probabilities for a Markovian Arrival Process (MMAP).
mmap_sigma2_cell(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_sigma2Kt
Computes two-step class transition probabilities for a Markovian Arrival Process (MMAP).
Mmap_sigma2Kt - class in jline.api.mam
 
Mmap_sigmaKt - class in jline.api.mam
 
mmap_sum(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_sumKt
Computes the sum of two MMAPs, creating a superposition process.
mmap_sum_multiple(java.util.List) - function in jline.api.mam.Mmap_sumKt
Computes the sum of multiple MMAPs.
mmap_sum_selective(java.util.List,java.util.List) - function in jline.api.mam.Mmap_sumKt
Selective sum - only sum specific classes from each MMAP.
mmap_sum_weighted(java.util.List,kotlin.DoubleArray) - function in jline.api.mam.Mmap_sumKt
Weighted sum of MMAPs with scaling factors.
Mmap_sumKt - class in jline.api.mam
 
mmap_super(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_superKt
Combines a list of MMAPs into one superposed MMAP.
mmap_super(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_superKt
Combines two MMAPs into one superposed MMAP using the default option.
mmap_super(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,java.lang.String) - function in jline.api.mam.Mmap_superKt
Combines two MMAPs into one superposed MMAP.
mmap_super_safe(java.util.Map,java.lang.Integer,java.lang.String) - function in jline.api.mam.Mmap_super_safeKt
 
Mmap_super_safeKt - class in jline.api.mam
 
Mmap_superKt - class in jline.api.mam
 
mmap_timereverse(jline.util.matrix.MatrixCell) - function in jline.api.mam.Mmap_timereverseKt
Computes the time-reversed version of a Markovian Arrival Process with marked arrivals (MMAP).
Mmap_timereverseKt - class in jline.api.mam
 
MmapBackwardMomentAlgo - class in jline.api.mam
MMAP backward moment algorithms
MmapCompressAlgo - class in jline.api.mam
MMAP compress algorithms
MmapCountIdcAlgo - class in jline.api.mam
MMAP count idc algorithms
MmapCountLambdaAlgo - class in jline.api.mam
MMAP count lambda algorithms
MmapCountMcovAlgo - class in jline.api.mam
MMAP count mcov algorithms
MmapCountMeanAlgo - class in jline.api.mam
MMAP count mean algorithms
MmapCountVarAlgo - class in jline.api.mam
MMAP count var algorithms
MmapCrossMomentAlgo - class in jline.api.mam
MMAP cross moment algorithms
MmapEmbeddedAlgo - class in jline.api.mam
MMAP embedded algorithms
MmapExponentialAlgo - class in jline.api.mam
MMAP exponential algorithms
MmapForwardMomentAlgo - class in jline.api.mam
MMAP forward moment algorithms
MmapHideAlgo - class in jline.api.mam
MMAP hide algorithms
MmapIdcAlgo - class in jline.api.mam
MMAP idc algorithms
MmapIsfeasibleAlgo - class in jline.api.mam
MMAP isfeasible algorithms
MmapIssymAlgo - class in jline.api.mam
MMAP issym algorithms
MMAPKPHK1Options - class in jline.lib.qmam
Options for MMAPK/PHK/1 queue analysis
MMAPKPHK1Result - class in jline.lib.qmam
Result of MMAPK/PHK/1 queue analysis
MmapLambdaAlgo - class in jline.api.mam
MMAP lambda algorithms
MmapMapsAlgo - class in jline.api.mam
MMAP maps algorithms
MmapMark - class in jline.api.mam
MMAP mark algorithms
MmapMaxAlgo - class in jline.api.mam
MMAP max algorithms
MmapMixtureAlgo - class in jline.api.mam
MMAP mixture algorithms
MmapMixtureFitAlgo - class in jline.api.mam
MMAP mixture fit algorithms
MmapMixtureFitMmapAlgo - class in jline.api.mam
MMAP mixture fit mmap algorithms
MmapMixtureFitTraceAlgo - class in jline.api.mam
MMAP mixture fit trace algorithms
MmapMixtureOrder2Algo - class in jline.api.mam
MMAP mixture order2 algorithms
MmapModulateAlgo - class in jline.api.mam
MMAP modulate algorithms
MmapNormalizeAlgo - class in jline.api.mam
MMAP normalize algorithms
MmapPcAlgo - class in jline.api.mam
MMAP pc algorithms
MMAPPH1FCFS(jline.util.matrix.MatrixCell,java.util.Map,java.util.Map,java.lang.Integer,java.lang.Integer,java.lang.Integer,jline.util.matrix.Matrix,java.lang.Boolean,java.lang.Boolean,java.lang.Double,jline.util.matrix.Matrix) - function in jline.lib.butools.MMAPPH1FCFSKt
 
MMAPPH1FCFSKt - class in jline.lib.butools
 
MMAPPH1NPPR(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Integer,java.lang.Integer,jline.util.matrix.Matrix,java.lang.Double,java.lang.Integer,jline.util.matrix.Matrix) - function in jline.lib.butools.MMAPPH1NPPRKt
 
MMAPPH1NPPRKt - class in jline.lib.butools
 
MMAPPH1PRPR(jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Integer,java.lang.Integer,jline.util.matrix.Matrix,java.lang.Double,java.lang.Integer,jline.util.matrix.Matrix) - function in jline.lib.butools.MMAPPH1PRPRKt
Analyzes multi-class MMAPK/PHK/1 queue with preemptive-resume (PRPR) priority.
MMAPPH1PRPRKt - class in jline.lib.butools
 
MmapPieAlgo - class in jline.api.mam
MMAP pie algorithms
MmapRandAlgo - class in jline.api.mam
MMAP rand algorithms
MmapSampleAlgo - class in jline.api.mam
MMAP sample algorithms
MmapScale - class in jline.api.mam
MMAP scale algorithms
MmapShortenAlgo - class in jline.api.mam
MMAP shorten algorithms
MmapSigma2Algo - class in jline.api.mam
MMAP sigma2 algorithms
MmapSigmaAlgo - class in jline.api.mam
MMAP sigma algorithms
MmapSum - class in jline.api.mam
MMAP sum algorithms
MmapSuperAlgo - class in jline.api.mam
MMAP super algorithms
MmapSuperSafeAlgo - class in jline.api.mam
MMAP super safe algorithms
MmapTimereverse - class in jline.api.mam
MMAP timereverse algorithms
MMDP - class in jline.lang.processes
A Markov-Modulated Deterministic Process (MMDP) for fluid queue modeling.
MMPP2 - enum entry in jline.lang.constant.ProcessType
 
MMPP2 - class in jline.lang.processes
A Markovian-modulated Poisson Process with 2 states
mmpp2_fit(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitKt
Fits a 2-phase Markovian Arrival Process (MMPP2) to match the given first three moments and a fourth parameter G2.
mmpp2_fit(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits a 2-state MMPP (MMPP2) to match first three moments and lag-1 autocorrelation.
mmpp2_fit1(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fit1Kt
Fits a 2-phase Markov Modulated Poisson Process (MMPP2) based on the specified parameters.
mmpp2_fit1(java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits MMPP2 using only moments (no autocorrelation).
Mmpp2_fit1Kt - class in jline.api.mam
 
mmpp2_fit2(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits MMPP2 using moments and lag-1 ACF.
mmpp2_fit3(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits MMPP2 using moments and lag-2 ACF (approximation).
mmpp2_fit4(java.lang.Double,java.lang.Double,java.lang.Double,kotlin.DoubleArray) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits MMPP2 using moments and multiple ACF lags.
Mmpp2_fit_count - class in jline.api.mam
Fits a MMPP(2) according to Heffes and Lucantoni, 1986.
mmpp2_fit_count(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fit_count.Companion
 
Mmpp2_fit_count_approx - class in jline.api.mam
Fits a second-order Marked MMPP using optimization.
mmpp2_fit_count_approx(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fit_count_approx.Companion
 
mmpp2_fit_example() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 Fit Example Source: MMPP2_fit_example.
mmpp2_fit_mu00(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitKt
 
mmpp2_fit_mu11(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitKt
 
mmpp2_fit_q01(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitKt
 
mmpp2_fit_q10(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitKt
 
Mmpp2_fitc - class in jline.api.mam
Fits a MMPP(2) according to Heffes and Lucantoni, 1986.
mmpp2_fitc(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitc.Companion
 
mmpp2_fitc(java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits MMPP2 from counting process statistics.
Mmpp2_fitc_approx - class in jline.api.mam
Fits a second-order Marked MMPP using optimization.
mmpp2_fitc_approx(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.api.mam.Mmpp2_fitc_approx.Companion
 
mmpp2_fitc_approx(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Fits MMPP2 from counting process with approximation.
mmpp2_fitc_theoretical(java.lang.Double,java.lang.Double,java.lang.Double,java.lang.Double) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Theoretical MMPP2 fitting from counting process.
Mmpp2_fitKt - class in jline.api.mam
 
mmpp2_lrd() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 LRD (Long Range Dependent) model Source: MMPP2_lrd.
mmpp2_markov_example() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 Markov Example Source: MMPP2_markov_example.
mmpp2_noacf() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 NoACF (No Autocorrelation Function) model Source: MMPP2_noacf.
mmpp2_simple() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 Simple Example Source: MMPP2_simple.
mmpp2_srd() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 SRD (Short Range Dependent) model Source: MMPP2_srd.
mmpp2_trace_example() - function in jline.lib.kpctoolbox.MAPCatalog
MMPP2 Trace Example Source: MMPP2_trace_example.
Mmpp2Fit1Algo - class in jline.api.mam
Mmpp2 Fit1 algorithms
Mmpp2FitAlgo - class in jline.api.mam
Mmpp2 Fit algorithms
Mmpp2FitcAlgo - class in jline.api.mam
Mmpp2 Fitc algorithms
Mmpp2FitCountApproxAlgo - class in jline.api.mam
Mmpp2 Fit Count Approx algorithms
mmpp_rand() - function in jline.api.mam.Mmpp_randKt
Generates a random Markov Modulated Poisson Process (MMPP) with 2 states.
mmpp_rand(java.lang.Integer) - function in jline.api.mam.Mmpp_randKt
Generates a random Markov Modulated Poisson Process (MMPP) with K states.
mmpp_rand(jline.util.matrix.MatrixCell,java.lang.Integer,java.lang.Long) - function in jline.lib.kpctoolbox.mmpp.MMPPKt
Generates random samples from an MMPP.
Mmpp_randKt - class in jline.api.mam
 
MMPPKt - class in jline.lib.kpctoolbox.mmpp
 
MmppRandAlgo - class in jline.api.mam
Mmpp Rand algorithms
mmt(jline.lang.Network) - function in jline.lang.ModelAdapter
Fork-Join Transform approach with default forkLambda parameter
mmt(jline.lang.Network,jline.util.matrix.Matrix) - function in jline.lang.ModelAdapter
Fork-Join Transform approach to evaluate queueing networks including fork-join systems.
MockOtlpReceiver - class in jline.streaming
Mock OTLP gRPC receiver for testing streaming functionality.
Mode - class in jline.lang
Superclass representing a class of jobs
mode(jline.streaming.StreamingOptions.StreamMode) - function in jline.streaming.StreamingOptions
Set the streaming mode.
ModeEvent - class in jline.lang
A mode event occurring in a Network.
Model - class in jline.lang
Class representing a model supported by the library
model() - function in jline.solvers.NetworkSolver
 
model() - function in jline.solvers.NetworkSolver
 
ModelAdapter - class in jline.lang
Static class to transform and adapt models, providing functionality for: - Creating tagged job models for response time analysis - Fork-join network transformations (formerly from FJ.
ModelAdapter.AggregateChainResult - class in jline.lang.ModelAdapter
Result of aggregating chains in a model
ModelAdapter.DeaggInfo - class in jline.lang.ModelAdapter
Deaggregation information for converting chain-level results back to class-level
ModelAdapter.TaggedChainResult - class in jline.lang.ModelAdapter
Result of tagging a chain in a model
ModelAnalyzer - class in jline.solvers.auto
Helper class to analyze model characteristics for solver selection
ModifyMode - class in jline.api.sn
Modification mode for SN setter methods.
moments() - function in jline.lang.processes.Markovian
Kotlin-style property alias for getMoments()
moments() - function in jline.lang.processes.Markovian
Kotlin-style property alias for getMoments()
moments(org.apache.commons.math3.analysis.UnivariateFunction,java.lang.Integer) - function in jline.lib.lti.cme
 
momentsFromDPH(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.dph.MomentsFromDPHKt
Returns the first K moments of a discrete phase-type distribution.
momentsFromDPH(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.butools.dph.MomentsFromDPHKt
Returns the first K moments of a discrete phase-type distribution.
momentsFromDPH(kotlin.DoubleArray,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.dph.MomentsFromDPHKt
Overload for DoubleArray alpha.
momentsFromDPH(kotlin.DoubleArray,jline.util.matrix.Matrix) - function in jline.lib.butools.dph.MomentsFromDPHKt
Overload for DoubleArray alpha.
MomentsFromDPHKt - class in jline.lib.butools.dph
 
momentsFromME(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.ph.MomentsFromMEKt
Returns the first K moments of a matrix-exponential distribution.
momentsFromME(kotlin.DoubleArray,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.ph.MomentsFromMEKt
Overload for DoubleArray alpha.
MomentsFromMEKt - class in jline.lib.butools.ph
 
momentsFromMG(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.dph.MomentsFromMGKt
Returns the first K moments of a matrix-geometric distribution.
momentsFromMG(kotlin.DoubleArray,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.dph.MomentsFromMGKt
Overload for DoubleArray alpha.
MomentsFromMGKt - class in jline.lib.butools.dph
 
momentsFromPH(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.ph.MomentsFromMEKt
Returns the first K moments of a phase-type distribution.
momentsFromPH(kotlin.DoubleArray,jline.util.matrix.Matrix,java.lang.Integer) - function in jline.lib.butools.ph.MomentsFromMEKt
Overload for DoubleArray alpha.
MomsFromFactorialMoms(jline.util.matrix.Matrix) - function in jline.lib.butools.MomsFromFactorialMomsKt
 
MomsFromFactorialMomsKt - class in jline.lib.butools
 
momsFromHankelMoms(jline.util.matrix.Matrix) - function in jline.lib.butools.MomsFromHankelMomsKt
Returns the raw moments given the Hankel moments.
MomsFromHankelMomsKt - class in jline.lib.butools
 
momsFromNormMoms(jline.util.matrix.Matrix) - function in jline.lib.butools.MomsFromNormMomsKt
Returns the raw moments given the normalized moments.
MomsFromNormMomsKt - class in jline.lib.butools
 
momsFromReducedMoms(jline.util.matrix.Matrix) - function in jline.lib.butools.MomsFromReducedMomsKt
Returns the raw moments given the reduced moments.
MomsFromReducedMomsKt - class in jline.lib.butools
 
MomSolver - class in jline.lib.mom.solver
Method of Moments (MOM) solver for queueing network analysisThis solver implements the MOM algorithm for computing performance measures of closed queueing networks with multiple classes and servers.
MomSolverResult - class in jline.lib.mom.solver
Result container for MOM solver computations
MomUtils - class in jline.lib.mom.util
MOM-specific utility functions for combinatorial operations Complements the existing jline.util.
mqn_basic() - function in jline.examples.java.basic.MixedExamples
Basic mixed open/closed network (mqn_basic.ipynb).
mqn_basic() - function in jline.examples.java.basic.MixedModel
Simple mixed open/closed network with delay and PS queue.
mqn_multiserver_fcfs() - function in jline.examples.java.basic.MixedExamples
Mixed network with FCFS multi-server queues (mqn_multiserver_fcfs.ipynb).
mqn_multiserver_fcfs() - function in jline.examples.java.basic.MixedModel
Mixed network similar to example 2 but with FCFS scheduling.
mqn_multiserver_ps() - function in jline.examples.java.basic.MixedExamples
Mixed network with PS multi-server queues (mqn_multiserver_ps.ipynb).
mqn_multiserver_ps() - function in jline.examples.java.basic.MixedModel
Complex mixed network with five PS queues and different server counts.
mqn_singleserver_fcfs() - function in jline.examples.java.basic.MixedExamples
Mixed FCFS network with large closed population (mqn_singleserver_fcfs.ipynb).
mqn_singleserver_fcfs() - function in jline.examples.java.basic.MixedModel
Mixed network with large closed class population and APH arrivals.
mqn_singleserver_ps() - function in jline.examples.java.basic.MixedExamples
Mixed PS network with simplified routing (mqn_singleserver_ps.ipynb).
mqn_singleserver_ps() - function in jline.examples.java.basic.MixedModel
Mixed PS network with large closed population and simplified open routing.
MQNResultsFormatter - class in jline.bench.mqn
Formats MQN benchmark results in MATLAB-style output format
MQNResultsFormatter.MQNBenchmarkResult - class in jline.bench.mqn.MQNResultsFormatter
Benchmark result data structure
MQNResultsFormatter.MQNResultsAccumulator - class in jline.bench.mqn.MQNResultsFormatter
Accumulates benchmark results for batch formatting
ms_additivesymmetricchisquared(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_additivesymmetricchisquaredKt
Additive symmetric chi-squared distance between two probability distributions.
Ms_additivesymmetricchisquaredKt - class in jline.api.measures
 
ms_anderson_darling(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_anderson_darlingKt
Anderson-Darling distance between two empirical distributions.
Ms_anderson_darlingKt - class in jline.api.measures
 
ms_avgl1linfty(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_avgl1linftyKt
Average L1 L-infinity distance between two probability distributions.
Ms_avgl1linftyKt - class in jline.api.measures
 
ms_bhattacharyya(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_bhattacharyyaKt
Bhattacharyya distance between two probability distributions.
Ms_bhattacharyyaKt - class in jline.api.measures
 
ms_canberra(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_canberraKt
Canberra distance between two probability distributions.
Ms_canberraKt - class in jline.api.measures
 
ms_chebyshev(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_chebyshevKt
Chebyshev distance between two probability distributions.
Ms_chebyshevKt - class in jline.api.measures
 
ms_cityblock(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_cityblockKt
City block (Manhattan) distance between two probability distributions.
Ms_cityblockKt - class in jline.api.measures
 
ms_clark(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_clarkKt
Clark distance between two probability distributions.
Ms_clarkKt - class in jline.api.measures
 
ms_condentropy(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_condentropyKt
Compute conditional entropy z=H(x|y) of two discrete variables x and y.
Ms_condentropyKt - class in jline.api.measures
 
ms_cosine(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_cosineKt
Cosine distance between two probability distributions.
Ms_cosineKt - class in jline.api.measures
 
ms_cramer_von_mises(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_cramer_von_misesKt
Cramér-von Mises distance between two empirical distributions.
Ms_cramer_von_misesKt - class in jline.api.measures
 
ms_czekanowski(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_czekanowskiKt
Czekanowski distance between two probability distributions.
Ms_czekanowskiKt - class in jline.api.measures
 
ms_dice(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_diceKt
Dice distance between two probability distributions.
Ms_diceKt - class in jline.api.measures
 
ms_divergence(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_divergenceKt
Divergence distance between two probability distributions.
Ms_divergenceKt - class in jline.api.measures
 
ms_entropy(jline.util.matrix.Matrix) - function in jline.api.measures.Ms_entropyKt
Compute entropy z=H(x) of a discrete variable x.
Ms_entropyKt - class in jline.api.measures
 
ms_euclidean(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_euclideanKt
Euclidean distance between two probability distributions.
Ms_euclideanKt - class in jline.api.measures
 
ms_fidelity(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_fidelityKt
Fidelity distance between two probability distributions.
Ms_fidelityKt - class in jline.api.measures
 
ms_gower(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_gowerKt
Gower distance between two probability distributions.
Ms_gowerKt - class in jline.api.measures
 
ms_harmonicmean(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_harmonicmeanKt
Harmonic mean distance between two probability distributions.
Ms_harmonicmeanKt - class in jline.api.measures
 
ms_hellinger(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_hellingerKt
Hellinger distance between two probability distributions.
Ms_hellingerKt - class in jline.api.measures
 
ms_intersection(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_intersectionKt
Intersection distance between two probability distributions.
Ms_intersectionKt - class in jline.api.measures
 
ms_jaccard(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_jaccardKt
Jaccard distance between two probability distributions.
Ms_jaccardKt - class in jline.api.measures
 
ms_jeffreys(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_jeffreysKt
Jeffreys divergence between two probability distributions.
Ms_jeffreysKt - class in jline.api.measures
 
ms_jensendifference(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_jensendifferenceKt
Jensen difference divergence between two probability distributions.
Ms_jensendifferenceKt - class in jline.api.measures
 
ms_jensenshannon(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_jensenshannonKt
Jensen-Shannon divergence between two probability distributions.
Ms_jensenshannonKt - class in jline.api.measures
 
ms_jointentropy(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_jointentropyKt
Compute joint entropy z=H(x,y) of two discrete variables x and y.
Ms_jointentropyKt - class in jline.api.measures
 
ms_kdivergence(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kdivergenceKt
K-divergence between two probability distributions.
Ms_kdivergenceKt - class in jline.api.measures
 
ms_kolmogorov_smirnov(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kolmogorov_smirnovKt
Kolmogorov-Smirnov distance between two empirical distributions.
Ms_kolmogorov_smirnovKt - class in jline.api.measures
 
ms_kuiper(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kuiperKt
Kuiper distance between two empirical distributions.
Ms_kuiperKt - class in jline.api.measures
 
ms_kulczynskid(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kulczynskidKt
Kulczynski d distance between two probability distributions.
Ms_kulczynskidKt - class in jline.api.measures
 
ms_kulczynskis(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kulczynskisKt
Kulczynski s distance between two probability distributions.
Ms_kulczynskisKt - class in jline.api.measures
 
ms_kullbackleibler(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kullbackleiblerKt
Kullback-Leibler divergence between two probability distributions.
Ms_kullbackleiblerKt - class in jline.api.measures
 
ms_kumarhassebrook(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kumarhassebrookKt
Kumar-Hassebrook distance between two probability distributions.
Ms_kumarhassebrookKt - class in jline.api.measures
 
ms_kumarjohnson(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_kumarjohnsonKt
Kumar-Johnson distance between two probability distributions.
Ms_kumarjohnsonKt - class in jline.api.measures
 
ms_lorentzian(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_lorentzianKt
Lorentzian distance between two probability distributions.
Ms_lorentzianKt - class in jline.api.measures
 
ms_matusita(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_matusitaKt
Matusita distance between two probability distributions.
Ms_matusitaKt - class in jline.api.measures
 
ms_minkowski(jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Double) - function in jline.api.measures.Ms_minkowskiKt
Minkowski distance between two probability distributions.
Ms_minkowskiKt - class in jline.api.measures
 
ms_motyka(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_motykaKt
Motyka distance between two probability distributions.
Ms_motykaKt - class in jline.api.measures
 
ms_mutinfo(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_mutinfoKt
Compute mutual information I(x,y) of two discrete variables x and y.
Ms_mutinfoKt - class in jline.api.measures
 
ms_neymanchisquared(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_neymanchisquaredKt
Neyman chi-squared distance between two probability distributions.
Ms_neymanchisquaredKt - class in jline.api.measures
 
Ms_nmi - class in jline.api.measures
Ms_nmi algorithms
ms_nmi(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_nmiKt
Compute normalized mutual information I(x,y)/sqrt(H(x)*H(y)) of two discrete variables x and y.
Ms_nmiKt - class in jline.api.measures
 
Ms_nvi - class in jline.api.measures
Ms_nvi algorithms
ms_nvi(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_nviKt
Compute normalized variation information z=(1-I(x,y)/H(x,y)) of two discrete variables x and y.
Ms_nviKt - class in jline.api.measures
 
ms_pearsonchisquared(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_pearsonchisquaredKt
Pearson chi-squared distance between two probability distributions.
Ms_pearsonchisquaredKt - class in jline.api.measures
 
ms_probsymmchisquared(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_probsymmchisquaredKt
Probabilistic symmetry chi-squared distance between two probability distributions.
Ms_probsymmchisquaredKt - class in jline.api.measures
 
ms_product(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_productKt
Product distance between two probability distributions.
Ms_productKt - class in jline.api.measures
 
ms_relatentropy(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_relatentropyKt
Compute relative entropy (a.k.a KL divergence) z=KL(p(x)||p(y)) of two discrete variables x and y.
Ms_relatentropyKt - class in jline.api.measures
 
ms_ruzicka(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_ruzickaKt
Ruzicka distance between two probability distributions.
Ms_ruzickaKt - class in jline.api.measures
 
ms_soergel(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_soergelKt
Soergel distance between two probability distributions.
Ms_soergelKt - class in jline.api.measures
 
ms_sorensen(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_sorensenKt
Sorensen distance between two probability distributions.
Ms_sorensenKt - class in jline.api.measures
 
ms_squaredchisquared(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_squaredchisquaredKt
Squared chi-squared distance between two probability distributions.
Ms_squaredchisquaredKt - class in jline.api.measures
 
ms_squaredchord(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_squaredchordKt
Squared chord distance between two probability distributions.
Ms_squaredchordKt - class in jline.api.measures
 
ms_squaredeuclidean(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_squaredeuclideanKt
Squared Euclidean distance between two probability distributions.
Ms_squaredeuclideanKt - class in jline.api.measures
 
ms_taneja(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_tanejaKt
Taneja distance between two probability distributions.
Ms_tanejaKt - class in jline.api.measures
 
ms_tanimoto(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_tanimotoKt
Tanimoto distance between two probability distributions.
Ms_tanimotoKt - class in jline.api.measures
 
ms_topsoe(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_topsoeKt
Topsoe distance between two probability distributions.
Ms_topsoeKt - class in jline.api.measures
 
ms_wasserstein(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_wassersteinKt
Wasserstein distance (Earth Mover's Distance) between two empirical distributions.
Ms_wassersteinKt - class in jline.api.measures
 
ms_wavehegdes(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.api.measures.Ms_wavehegdesKt
Wave-Hedges distance between two probability distributions.
Ms_wavehegdesKt - class in jline.api.measures
 
MsAdditivesymmetricchisquaredAlgo - class in jline.api.measures
Additivesymmetricchisquared metric algorithms
MsAvgl1linftyAlgo - class in jline.api.measures
Avgl1Linfty metric algorithms
MsBhattacharyyaAlgo - class in jline.api.measures
Bhattacharyya metric algorithms
MsCanberraAlgo - class in jline.api.measures
Canberra metric algorithms
MsChebyshevAlgo - class in jline.api.measures
Chebyshev metric algorithms
MsCityblockAlgo - class in jline.api.measures
Cityblock metric algorithms
MsClarkAlgo - class in jline.api.measures
Clark metric algorithms
MsCosineAlgo - class in jline.api.measures
Cosine metric algorithms
MsCzekanowskiAlgo - class in jline.api.measures
Czekanowski metric algorithms
MsDiceAlgo - class in jline.api.measures
Dice metric algorithms
MsDivergenceAlgo - class in jline.api.measures
Divergence metric algorithms
MsEuclideanAlgo - class in jline.api.measures
Euclidean distance metric algorithms
MsFidelityAlgo - class in jline.api.measures
Fidelity metric algorithms
MsGowerAlgo - class in jline.api.measures
Gower metric algorithms
MsHarmonicmeanAlgo - class in jline.api.measures
Harmonicmean metric algorithms
MsHellingerAlgo - class in jline.api.measures
Hellinger metric algorithms
MsIntersectionAlgo - class in jline.api.measures
Intersection metric algorithms
MsJaccardAlgo - class in jline.api.measures
Jaccard metric algorithms
MsJeffreysAlgo - class in jline.api.measures
Jeffreys metric algorithms
MsJensendifferenceAlgo - class in jline.api.measures
Jensendifference metric algorithms
MsJensenshannonAlgo - class in jline.api.measures
Jensenshannon metric algorithms
MsKdivergenceAlgo - class in jline.api.measures
Kdivergence metric algorithms
MsKulczynskidAlgo - class in jline.api.measures
Kulczynskid metric algorithms
MsKulczynskisAlgo - class in jline.api.measures
Kulczynskis metric algorithms
MsKullbackleiblerAlgo - class in jline.api.measures
Kullbackleibler metric algorithms
MsKumarhassebrookAlgo - class in jline.api.measures
Kumarhassebrook metric algorithms
MsKumarjohnsonAlgo - class in jline.api.measures
Kumarjohnson metric algorithms
MsLorentzianAlgo - class in jline.api.measures
Lorentzian metric algorithms
MsMatusitaAlgo - class in jline.api.measures
Matusita metric algorithms
MsMinkowskiAlgo - class in jline.api.measures
Minkowski metric algorithms
MsMotykaAlgo - class in jline.api.measures
Motyka metric algorithms
MsNeymanchisquaredAlgo - class in jline.api.measures
Neymanchisquared metric algorithms
MsPearsonchisquaredAlgo - class in jline.api.measures
Pearsonchisquared metric algorithms
MsProductAlgo - class in jline.api.measures
Product metric algorithms
MsRuzickaAlgo - class in jline.api.measures
Ruzicka metric algorithms
MsSoergelAlgo - class in jline.api.measures
Soergel metric algorithms
MsSorensenAlgo - class in jline.api.measures
Sorensen metric algorithms
MsSquaredchisquaredAlgo - class in jline.api.measures
Squaredchisquared metric algorithms
MsSquaredchordAlgo - class in jline.api.measures
Squaredchord metric algorithms
MsSquaredeuclideanAlgo - class in jline.api.measures
Squaredeuclidean metric algorithms
MsTanejaAlgo - class in jline.api.measures
Taneja metric algorithms
MsTanimotoAlgo - class in jline.api.measures
Tanimoto metric algorithms
MsTopsoeAlgo - class in jline.api.measures
Topsoe metric algorithms
MsWavehegdesAlgo - class in jline.api.measures
Wavehegdes metric algorithms
MTrace - class in jline.lib.m3a
Data structure for multiclass trace representation.
mtrace_backward_moment(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer,java.lang.Integer) - function in jline.api.trace.Mtrace_backward_momentKt
Computes backward moments of a multi-class trace.
mtrace_backward_moment_conditional(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer,java.lang.Integer) - function in jline.api.trace.Mtrace_backward_momentKt
Computes conditional backward moments given the forward recurrence time.
Mtrace_backward_momentKt - class in jline.api.trace
 
mtrace_bootstrap(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer,java.lang.Integer,java.lang.Long) - function in jline.api.trace.Mtrace_bootstrapKt
Performs bootstrap resampling on a multi-class trace to estimate confidence intervals and assess variability of trace statistics.
Mtrace_bootstrapKt - class in jline.api.trace
 
mtrace_count(kotlin.DoubleArray,kotlin.IntArray,java.lang.Double,java.lang.Integer) - function in jline.api.trace.Mtrace_countKt
Computes count statistics from a multi-class trace over specified time windows.
mtrace_count_multiscale(kotlin.DoubleArray,kotlin.IntArray,kotlin.DoubleArray) - function in jline.api.trace.Mtrace_countKt
Compute multi-scale count statistics
Mtrace_countKt - class in jline.api.trace
 
mtrace_cov(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_covKt
Computes the covariance matrix for multi-type traces.
Mtrace_covKt - class in jline.api.trace
 
mtrace_cross_moment(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer) - function in jline.api.mam.Mmap_mixture_fit_traceKt
Computes cross-class moments of given order from trace.
mtrace_cross_moment(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer) - function in jline.api.trace.Mtrace_cross_momentKt
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.
Mtrace_cross_momentKt - class in jline.api.trace
 
mtrace_forward_moment(kotlin.DoubleArray,kotlin.IntArray,kotlin.IntArray,java.lang.Integer) - function in jline.api.trace.Mtrace_forward_momentKt
Computes the forward moments of a marked trace.
Mtrace_forward_momentKt - class in jline.api.trace
 
mtrace_iat2counts(kotlin.DoubleArray,kotlin.IntArray,java.lang.Double) - function in jline.api.mam.m3pp.M3pp2m_fitc_traceKt
Converts inter-arrival times to counts at given resolution.
mtrace_iat2counts(kotlin.DoubleArray,java.lang.Double) - function in jline.api.trace.Mtrace_countKt
Convert inter-arrival times to count process using native implementation equivalent
mtrace_iat2counts(kotlin.DoubleArray,kotlin.IntArray,java.lang.Double) - function in jline.api.trace.Mtrace_iat2countsKt
Computes the per-class counting processes of T, i.e., the counts after "scale" units of time from an arrival.
Mtrace_iat2countsKt - class in jline.api.trace
 
mtrace_joint(kotlin.DoubleArray,kotlin.IntArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_jointKt
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.
Mtrace_jointKt - class in jline.api.trace
 
mtrace_mean(kotlin.DoubleArray,java.lang.Integer,kotlin.IntArray) - function in jline.api.trace.Mtrace_meanKt
Computes the mean of a trace, divided by types.
mtrace_mean(java.util.List) - function in jline.lib.kpctoolbox.trace.TraceAnalysisKt
Computes the mean of multiple traces (multi-trace mean).
Mtrace_meanKt - class in jline.api.trace
 
mtrace_merge(kotlin.DoubleArray,kotlin.DoubleArray) - function in jline.api.trace.Mtrace_mergeKt
Merges two traces in a single marked (multiclass) trace
Mtrace_mergeKt - class in jline.api.trace
 
mtrace_moment(kotlin.DoubleArray,kotlin.IntArray,kotlin.IntArray,java.lang.Integer,java.lang.Integer) - function in jline.api.trace.Mtrace_momentKt
Computes the empirical class-dependent moments of a multi-class trace.
mtrace_moment_simple(kotlin.DoubleArray,kotlin.IntArray,java.lang.Integer) - function in jline.api.trace.Mtrace_moment_simpleKt
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.
Mtrace_moment_simpleKt - class in jline.api.trace
 
Mtrace_momentKt - class in jline.api.trace
 
mtrace_pc(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_pcKt
Computes the probabilities of arrival for each class.
Mtrace_pcKt - class in jline.api.trace
 
mtrace_sigma(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_sigmaKt
Computes the empirical probability of observing a specific 2-element sequence of events, i.e.
mtrace_sigma2(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.mam.Mmap_mixture_fit_traceKt
Computes two-step class transition probabilities from trace.
mtrace_sigma2(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_sigma2Kt
Computes the empirical probability of observing a specific 3-element sequence of events, i.e.
Mtrace_sigma2Kt - class in jline.api.trace
 
Mtrace_sigmaKt - class in jline.api.trace
 
mtrace_split(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_splitKt
Given a multi-class trace with inter-arrivals T and labels L, creates the separate per-class traces.
Mtrace_splitKt - class in jline.api.trace
 
mtrace_summary(kotlin.DoubleArray,kotlin.IntArray) - function in jline.api.trace.Mtrace_summaryKt
Computes comprehensive summary statistics for a multi-class trace.
Mtrace_summaryKt - class in jline.api.trace
 
MtraceBackwardMomentAlgo - class in jline.api.trace
Mtrace Backward Moment algorithms
MtraceBootstrapAlgo - class in jline.api.trace
Mtrace Bootstrap algorithms
MtraceCountAlgo - class in jline.api.trace
Mtrace Count algorithms
MtraceCovAlgo - class in jline.api.trace
Mtrace Cov algorithms
MtraceCrossMomentAlgo - class in jline.api.trace
Mtrace Cross Moment algorithms
MtraceForwardMomentAlgo - class in jline.api.trace
Mtrace Forward Moment algorithms
MtraceIat2countsAlgo - class in jline.api.trace
Mtrace Iat2Counts algorithms
MtraceJointAlgo - class in jline.api.trace
Mtrace Joint algorithms
MtraceMeanAlgo - class in jline.api.trace
Mtrace Mean algorithms
MtraceMergeAlgo - class in jline.api.trace
Mtrace Merge algorithms
MtraceMomentAlgo - class in jline.api.trace
Mtrace Moment algorithms
MtraceMomentSimpleAlgo - class in jline.api.trace
Mtrace Moment Simple algorithms
MtracePcAlgo - class in jline.api.trace
Mtrace Pc algorithms
MtraceSigma2Algo - class in jline.api.trace
Mtrace Sigma2 algorithms
MtraceSigmaAlgo - class in jline.api.trace
Mtrace Sigma algorithms
MtraceSplitAlgo - class in jline.api.trace
Mtrace Split algorithms
MtraceSummary - class in jline.api.trace
Data class representing a summary of multi-trace statistics
MtraceSummaryAlgo - class in jline.api.trace
Mtrace Summary algorithms
mu() - function in jline.lang.processes.Coxian
Kotlin-style property alias for getMu()
mu() - function in jline.lang.processes.Coxian
Kotlin-style property alias for getMu()
mu() - function in jline.lang.processes.Det
Kotlin-style property alias for getMu()
mu() - function in jline.lang.processes.Markovian
Kotlin-style property alias for getMu()
mu() - function in jline.lang.processes.Markovian
Kotlin-style property alias for getMu()
mulByMinusOne() - function in jline.util.matrix.Matrix
Multiplies all elements in the matrix by -1 in-place.
mult(org.ejml.data.DMatrix,org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.DenseMatrix
Performs matrix multiplication: output = A * B.
mult(jline.util.matrix.Matrix) - function in jline.util.matrix.Matrix
Performs matrix multiplication: this * B
mult(jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.util.matrix.Matrix
Performs matrix multiplication: this * B
mult(org.ejml.data.DMatrix,org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.SparseMatrix
Performs matrix multiplication: output = A * B.
multColumnView(jline.util.matrix.ColumnView) - function in jline.util.matrix.Matrix
Efficiently multiplies this row vector with a column view.
multEq(jline.util.matrix.Matrix) - function in jline.util.matrix.Matrix
Replaces this matrix with the result of this * B.
multichoose(double,double) - function in jline.util.Maths
 
multichoose(int,int) - function in jline.util.Maths
Generates all combinations of n objects taken k at a time with repetition (multichoose).
multiChooseCombinations(int,int) - function in jline.util.Maths
Generate all combinations of distributing n items into k bins
multiChooseCon(jline.util.matrix.Matrix,double) - function in jline.util.Maths
 
multichooseList(int,int) - function in jline.util.Maths
Generates all combinations of n objects taken k at a time with repetition (multichoose).
multiclassClosed() - function in jline.examples.java.advanced.AgentModel
Creates a multiclass closed network.
multinomialln(jline.util.matrix.Matrix) - function in jline.util.Maths
 
multiply(java.util.function.UnaryOperator) - function in jline.lib.lti.function_wrapper
 
multMatrix(org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.BaseMatrix
Performs matrix multiplication with sparse matrices.
multMatrix(org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.DenseMatrix
Performs matrix multiplication with sparse matrices.
multMatrix(org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.SparseMatrix
Performs matrix multiplication with sparse matrices.
multMatrixStatic(org.ejml.data.DMatrix,org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.DenseMatrix
 
multMatrixStatic(org.ejml.data.DMatrix,org.ejml.data.DMatrix,org.ejml.data.DMatrix) - function in jline.util.matrix.SparseMatrix
 
multRowView(jline.util.matrix.RowView) - function in jline.util.matrix.Matrix
Efficiently multiplies a row view with this column vector.
MVA - enum entry in jline.lang.constant.SolverType
 
MVA - class in jline.solvers.mva
MVA is an alias for SolverMVA (Mean Value Analysis solver).
MVAOptions - class in jline.solvers.mva
Configuration options for Mean Value Analysis (MVA) solver.
MVAResult - class in jline.solvers.mva
Result container for Mean Value Analysis (MVA) solver computations.
MVARunner - class in jline.solvers.mva.handlers
 
MVASolverHandler - class in jline.solvers.mva.handlers
 
MVAVersionParameters - class in jline.api.mapqn
Parameters for MVA version models
mvph_corr(kotlin.DoubleArray,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.kpctoolbox.mvph.MVPHKt
Computes the correlation of a bivariate PH distribution.
mvph_cov(kotlin.DoubleArray,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.kpctoolbox.mvph.MVPHKt
Computes the covariance of a bivariate PH distribution.
mvph_joint(kotlin.DoubleArray,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix,java.lang.Integer,java.lang.Integer) - function in jline.lib.kpctoolbox.mvph.MVPHKt
Computes the joint moment EX^n1 * Y^n2 of a bivariate phase-type distribution.
mvph_mean_x(kotlin.DoubleArray,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.kpctoolbox.mvph.MVPHKt
Computes the mean of the first variable in a bivariate PH distribution.
mvph_mean_y(kotlin.DoubleArray,jline.util.matrix.Matrix,jline.util.matrix.Matrix,jline.util.matrix.Matrix) - function in jline.lib.kpctoolbox.mvph.MVPHKt
Computes the mean of the second variable in a bivariate PH distribution.
MVPHKt - class in jline.lib.kpctoolbox.mvph
 
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