mapfit1.0.0 package

General phase-type distribution

Determine hyper-Erlang parameters

Create HErlang distribution

Hyper-Erlang distribution

k-lag correlation of MAP

Joint moments of MAP

Marginal moments of MAP

Generate MAP using the information on data

Create MAP

General Markovian arrival process

ErlangHMM for MAP with fixed phases

Hyper-Erlang distribution with a fixed phase

Convert from HErlang to GPH

Convert from ERHMM to MAP

Determine CF1 parameters

Determine CF1 parameters

Create CF1 with data information

Create CF1

Canonical phase-type distribution

Markov stationary

Create group data for map

Create data for map

Create group data for phase

Create data for phase with weighted sample

Probability density function of PH distribution

EM Options

Determine ERHMM parameters

Create ERHMM

ErlangHMM for MAP

Create GMMPP

GMMPP: Approximation for MAP

Generate GPH using the information on data

mapfit: PH/MAP Parameter Estimation

MAP fitting with grouped data

MAP fitting with point data

Create an MMPP

Create a bi-diagonal PH distribution

Create a Coxian PH distribution

Mean of PH distribution

Moments of PH distribution

Create GPH distribution

Create a tri-diagonal PH distribution

Variance of PH distribution

PH fitting with three moments

PH fitting with density function

PH fitting with grouped data

PH fitting with point data

Distribution function of PH distribution

Sampling of PH distributions