CRAN/E | SMM

SMM

Simulation and Estimation of Multi-State Discrete-Time Semi-Markov and 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. 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 1.0.2
Published 2020-01-31 1555 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks SMM results

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Maintainer

Maintainer

Nicolas Vergne

nicolas.vergne@univ-rouen.fr

Authors

Vlad Stefan Barbu
Caroline Berard
Dominique Cellier
Mathilde Sautreuil
Nicolas Vergne

Material

NEWS
Reference manual
Package source

Vignettes

SMM Vignette

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

SMM archive

Depends

seqinr
DiscreteWeibull

Suggests

utils