dsmmR: Estimation and Simulation of Drifting Semi-Markov Models

Performs parametric and non-parametric estimation and simulation of drifting semi-Markov processes. The definition of parametric and non-parametric model specifications is also possible. Furthermore, three different types of drifting semi-Markov models are considered. These models differ in the number of transition matrices and sojourn time distributions used for the computation of a number of semi-Markov kernels, which in turn characterize the drifting semi-Markov kernel. For the parametric model estimation and specification, several discrete distributions are considered for the sojourn times: Uniform, Poisson, Geometric, Discrete Weibull and Negative Binomial. The non-parametric model specification makes no assumptions about the shape of the sojourn time distributions. Semi-Markov models are described in: Barbu, V.S., Limnios, N. (2008) <doi:10.1007/978-0-387-73173-5>. Drifting Markov models are described in: Vergne, N. (2008) <doi:10.2202/1544-6115.1326>. Reliability indicators of Drifting Markov models are described in: Barbu, V. S., Vergne, N. (2019) <doi:10.1007/s11009-018-9682-8>.

Version: 1.0.1
Depends: R (≥ 2.10)
Imports: DiscreteWeibull
Suggests: utils, knitr, rmarkdown
Published: 2023-02-04
Author: Vlad Stefan Barbu ORCID iD [aut], Ioannis Mavrogiannis [aut, cre], Nicolas Vergne [aut]
Maintainer: Ioannis Mavrogiannis <mavrogiannis.ioa at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: dsmmR results

Documentation:

Reference manual: dsmmR.pdf

Downloads:

Package source: dsmmR_1.0.1.tar.gz
Windows binaries: r-devel: dsmmR_1.0.1.zip, r-release: dsmmR_0.0.96.zip, r-oldrel: dsmmR_1.0.1.zip
macOS binaries: r-release (arm64): dsmmR_1.0.1.tgz, r-oldrel (arm64): dsmmR_1.0.1.tgz, r-release (x86_64): dsmmR_0.0.96.tgz, r-oldrel (x86_64): dsmmR_0.0.96.tgz
Old sources: dsmmR archive

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