An object for which there exists a <code>loglik</code> attribute if
<code>sequences = NULL</code> or a <code>loglik</code> method otherwise.

Optional. A list of vectors representing the sequences for
which the AIC will be computed based on <code>x</code> using the method <code>loglik</code>.

sequences

Generic function computing the Akaike Information Criterion of
the model <code>x</code>, with the list of sequences <code>sequences</code>.

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.

aic: Akaike Information Criterion (AIC)

Description

Usage

Arguments

Value