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'))

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

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

BCpAug89 - Packet Trace Data

On CRAN:

3.04 score 1 stars 22 scripts 218 downloads 37 exports 6 dependencies

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

Target	Result	Date
Doc / Vignettes	OK	Nov 07 2024
R-4.5-win-x86_64	OK	Nov 07 2024
R-4.5-linux-x86_64	OK	Nov 07 2024
R-4.4-win-x86_64	OK	Nov 07 2024
R-4.4-mac-x86_64	OK	Nov 07 2024
R-4.4-mac-aarch64	OK	Nov 07 2024
R-4.3-win-x86_64	OK	Nov 07 2024
R-4.3-mac-x86_64	OK	Nov 07 2024
R-4.3-mac-aarch64	OK	Nov 07 2024

Exports:as.gph as.map cf1 cf1.param ctmc.st data.frame.map.group data.frame.map.time data.frame.phase.group data.frame.phase.time dphase emoptions erhmm gmmpp gph.param herlang herlang.param map map.acf map.jmoment map.mmoment map.param mapfit.group mapfit.point mmpp ph ph.bidiag ph.coxian ph.mean ph.moment ph.tridiag ph.var phfit.3mom phfit.density phfit.group phfit.point pphase rphase

Dependencies:cpp11 deformula lattice Matrix R6 Rcpp

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
mapfit: PH/MAP Parameter Estimation	mapfit-package mapfit
ErlangHMM for MAP with fixed phases	AERHMMClass
Hyper-Erlang distribution with a fixed phase	AHerlangClass
Convert from HErlang to GPH	as.gph
Convert from ERHMM to MAP	as.map
Packet Trace Data	BCpAug89
Create CF1	cf1
Create CF1 with data information	cf1.param
Determine CF1 parameters	cf1.param.linear
Determine CF1 parameters	cf1.param.power
Canonical phase-type distribution	CF1Class
Markov stationary	ctmc.st
Create group data for map	data.frame.map.group
Create data for map	data.frame.map.time
Create group data for phase	data.frame.phase.group
Create data for phase with weighted sample	data.frame.phase.time
Probability density function of PH distribution	dphase
EM Options	emoptions
Create ERHMM	erhmm
Determine ERHMM parameters	erhmm.param
ErlangHMM for MAP	ERHMMClass
Create GMMPP	gmmpp
GMMPP: Approximation for MAP	GMMPPClass
Generate GPH using the information on data	gph.param
General phase-type distribution	GPHClass
Create HErlang distribution	herlang
Determine hyper-Erlang parameters	herlang.param
Hyper-Erlang distribution	HErlangClass
Create MAP	map
k-lag correlation of MAP	map.acf
Joint moments of MAP	map.jmoment
Marginal moments of MAP	map.mmoment
Generate MAP using the information on data	map.param
General Markovian arrival process	MAPClass
MAP fitting with grouped data	mapfit.group
MAP fitting with point data	mapfit.point
Create an MMPP	mmpp
Create GPH distribution	ph
Create a bi-diagonal PH distribution	ph.bidiag
Create a Coxian PH distribution	ph.coxian
Mean of PH distribution	ph.mean
Moments of PH distribution	ph.moment
Create a tri-diagonal PH distribution	ph.tridiag
Variance of PH distribution	ph.var
PH fitting with three moments	phfit.3mom
PH fitting with density function	phfit.density
PH fitting with grouped data	phfit.group
PH fitting with point data	phfit.point
Distribution function of PH distribution	pphase
Sampling of PH distributions	rphase