Package: mapfit 1.0.0

mapfit: PH/MAP Parameter Estimation

Estimation methods for phase-type distribution (PH) and Markovian arrival process (MAP) from empirical data (point and grouped data) and density function. The tool is based on the following researches: Okamura et al. (2009) <doi:10.1109/TNET.2008.2008750>, Okamura and Dohi (2009) <doi:10.1109/QEST.2009.28>, Okamura et al. (2011) <doi:10.1016/j.peva.2011.04.001>, Okamura et al. (2013) <doi:10.1002/asmb.1919>, Horvath and Okamura (2013) <doi:10.1007/978-3-642-40725-3_10>, Okamura and Dohi (2016) <doi:10.15807/jorsj.59.72>.

Authors:Hiroyuki Okamura [aut, cre]

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mapfit.pdf |mapfit.html
mapfit/json (API)
NEWS

# Install 'mapfit' in R:
install.packages('mapfit', repos = c('https://okamumu.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/okamumu/mapfit/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

37 exports 1 stars 0.74 score 6 dependencies 22 scripts 274 downloads

Last updated 2 years agofrom:77fc2ab0b4. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 08 2024
R-4.5-win-x86_64OKSep 08 2024
R-4.5-linux-x86_64OKSep 08 2024
R-4.4-win-x86_64OKSep 08 2024
R-4.4-mac-x86_64OKSep 08 2024
R-4.4-mac-aarch64OKSep 08 2024
R-4.3-win-x86_64OKSep 08 2024
R-4.3-mac-x86_64OKSep 08 2024
R-4.3-mac-aarch64OKSep 08 2024

Exports:as.gphas.mapcf1cf1.paramctmc.stdata.frame.map.groupdata.frame.map.timedata.frame.phase.groupdata.frame.phase.timedphaseemoptionserhmmgmmppgph.paramherlangherlang.parammapmap.acfmap.jmomentmap.mmomentmap.parammapfit.groupmapfit.pointmmppphph.bidiagph.coxianph.meanph.momentph.tridiagph.varphfit.3momphfit.densityphfit.groupphfit.pointpphaserphase

Dependencies:cpp11deformulalatticeMatrixR6Rcpp

Readme and manuals

Help Manual

Help pageTopics
mapfit: PH/MAP Parameter Estimationmapfit-package mapfit
ErlangHMM for MAP with fixed phasesAERHMMClass
Hyper-Erlang distribution with a fixed phaseAHerlangClass
Convert from HErlang to GPHas.gph
Convert from ERHMM to MAPas.map
Packet Trace DataBCpAug89
Create CF1cf1
Create CF1 with data informationcf1.param
Determine CF1 parameterscf1.param.linear
Determine CF1 parameterscf1.param.power
Canonical phase-type distributionCF1Class
Markov stationaryctmc.st
Create group data for mapdata.frame.map.group
Create data for mapdata.frame.map.time
Create group data for phasedata.frame.phase.group
Create data for phase with weighted sampledata.frame.phase.time
Probability density function of PH distributiondphase
EM Optionsemoptions
Create ERHMMerhmm
Determine ERHMM parameterserhmm.param
ErlangHMM for MAPERHMMClass
Create GMMPPgmmpp
GMMPP: Approximation for MAPGMMPPClass
Generate GPH using the information on datagph.param
General phase-type distributionGPHClass
Create HErlang distributionherlang
Determine hyper-Erlang parametersherlang.param
Hyper-Erlang distributionHErlangClass
Create MAPmap
k-lag correlation of MAPmap.acf
Joint moments of MAPmap.jmoment
Marginal moments of MAPmap.mmoment
Generate MAP using the information on datamap.param
General Markovian arrival processMAPClass
MAP fitting with grouped datamapfit.group
MAP fitting with point datamapfit.point
Create an MMPPmmpp
Create GPH distributionph
Create a bi-diagonal PH distributionph.bidiag
Create a Coxian PH distributionph.coxian
Mean of PH distributionph.mean
Moments of PH distributionph.moment
Create a tri-diagonal PH distributionph.tridiag
Variance of PH distributionph.var
PH fitting with three momentsphfit.3mom
PH fitting with density functionphfit.density
PH fitting with grouped dataphfit.group
PH fitting with point dataphfit.point
Distribution function of PH distributionpphase
Sampling of PH distributionsrphase