SMM: Simulation and Estimation of Multi-State Discrete-Time Semi-Markov and Markov Models
Version 1.0.1

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) , Barbu, V.S., Limnios, N. (2008) and Trevezas, S., Limnios, N. (2011) . Estimation and simulation of discrete-time k-th order Markov chains are also considered.

Package details

AuthorVlad Stefan Barbu, Caroline Berard, Dominique Cellier, Mathilde Sautreuil and Nicolas Vergne
Date of publication2017-09-08 12:50:13 UTC
MaintainerNicolas Vergne <[email protected]>
Package repositoryView on CRAN
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SMM documentation built on Sept. 8, 2017, 5:04 p.m.