smmR - Simulation, Estimation and Reliability of Semi-Markov Models
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.
