simulate.mmfit

An object of class <code>mmfit</code>.

object

An integer or vector of integers (for multiple sequences)
specifying the length of the sequence(s).

nsim

Optional. <code>seed</code> for the random number generator.
If no <code>seed</code> is given, then seed is set by using the command
<code>set.seed(round(as.numeric(Sys.time()))</code>.

seed

further arguments passed to or from other methods.

Simulates sequences from a fitted Markov model.

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.

simulate.mmfit: Simulates Markov chains

Description

Usage

Arguments

Value

Details

See Also