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Packages that use DenseContPhaseVar | |
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jphase | This package provides capabilities for modeling Phase type distributions. |
jphase.fit | Provides capabilities for fitting Phase type distribution parameters from data. |
Uses of DenseContPhaseVar in jphase |
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Methods in jphase that return DenseContPhaseVar | |
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static DenseContPhaseVar |
DenseContPhaseVar.Coxian(int n,
double[] lambdas,
double[] probs)
Construcs a Phase-Type representation of a Coxian distribution with n phases |
static DenseContPhaseVar |
DenseContPhaseVar.Erlang(double lambda,
int n)
Constructs a Phase-Type representation of an Erlang distribution with rate lambda and n exponential phases |
static DenseContPhaseVar |
DenseContPhaseVar.ErlangCoxian(int n,
double p,
double lambdaY,
double lambdaX1,
double lambdaX2,
double px)
Construcs a Phase-Type representation of an ErlangCoxian distribution as defined by Osogami and Harchol in "Closed form solutions for mapping general distributions to quasi-minimal PH distributions", 2005. |
static DenseContPhaseVar |
DenseContPhaseVar.expo(double lambda)
Constructs a Phase-Type representation of an Exponential distribution with rate lambda |
static DenseContPhaseVar |
DenseContPhaseVar.HyperErlang(HyperErlangVar var)
Construcs a Phase-Type representation of a Hyper-Erlang distribution from a Dense representation of the same distribution |
static DenseContPhaseVar |
DenseContPhaseVar.HyperErlang(int k,
double[] lambdas,
int[] n,
double[] probs)
Constructs a Phase-Type representation of a Hyper-Erlang distribution with k erlang branches, its k rates and n number of phases per branch |
static DenseContPhaseVar |
DenseContPhaseVar.HyperExpo(double[] lambdas,
double[] probs)
Constructs a Phase Distribution that represents a HyperExponential distribution with the especified parameters |
Uses of DenseContPhaseVar in jphase.fit |
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Methods in jphase.fit that return DenseContPhaseVar | |
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DenseContPhaseVar |
EMPhaseFit.fit()
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DenseContPhaseVar |
EMHyperExpoFit.fit()
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DenseContPhaseVar |
EMHyperErlangFit.fit()
Returns a HyperErlang variable with the best fit, in the form of a Dense Continuous Phase variable |
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