CRAN/E | smmR

smmR

Simulation, Estimation and Reliability of Semi-Markov Models

Installation

About

Performs parametric and non-parametric estimation and simulation for multi-state discrete-time semi-Markov processes. For the parametric estimation, several discrete distributions are considered for the sojourn times: Uniform, Geometric, Poisson, Discrete Weibull and Negative Binomial. The non-parametric estimation concerns the sojourn time distributions, where no assumptions are done on the shape of distributions. Moreover, the estimation can be done on the basis of one or several sample paths, with or without censoring at the beginning or/and at the end of the sample paths. Reliability indicators such as reliability, maintainability, availability, BMP-failure rate, RG-failure rate, mean time to failure and mean time to repair are available as well. The implemented methods are described in Barbu, V.S., Limnios, N. (2008) doi:10.1007/978-0-387-73173-5, Barbu, V.S., Limnios, N. (2008) doi:10.1080/10485250701261913 and Trevezas, S., Limnios, N. (2011) doi:10.1080/10485252.2011.555543. Estimation and simulation of discrete-time k-th order Markov chains are also considered.

Key Metrics

Version 1.0.3
Published 2021-08-03 1005 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks smmR results

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Maintainer

Maintainer

Nicolas Vergne

nicolas.vergne@univ-rouen.fr

Authors

Vlad Stefan Barbu

aut

Caroline Berard

aut

Dominique Cellier

aut

Florian Lecocq

aut

Corentin Lothode

aut

Mathilde Sautreuil

aut

Nicolas Vergne

aut / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

Textile-Factory

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

smmR archive

Imports

DiscreteWeibull
Rcpp
seqinr

Suggests

utils
knitr
rmarkdown

LinkingTo

Rcpp
RcppArmadillo