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

Performs the drifting Markov models (DMM) which are
non-homogeneous Markov models designed for modeling the heterogeneities of
sequences in a more flexible way than homogeneous Markov chains or even
hidden Markov models. In this context, we developed an R package dedicated to
the estimation, simulation and the exact computation of associated reliability
of drifting Markov models. The implemented methods are described in
Vergne, N. (2008), <doi:10.2202/1544-6115.1326> and
Barbu, V.S., Vergne, N. (2019) <doi:10.1007/s11009-018-9682-8> .

Nicolas Vergne

drimmR

Estimation, Simulation and Reliability of Drifting Markov Models

Corentin Lothodé

Alexandre Seiller

Victor Mataigne

Arnaud Lefebvre

Annthomy Gilles

bic function

<dl><dt>x</dt>
<dd>An object for which the log-likelihood of the DMM can be computed.</dd>
<dt>sequences</dt>
<dd>A list of vectors representing the sequences for which the BIC will be computed based on <code>x</code>.</dd>
<dt>ncpu</dt>
<dd>Default=2. Represents the number of cores used to parallelized computation. If ncpu=-1, then it uses all available cores.</dd></dl>

Arguments

Victor Mataigne, Alexandre Seiller

Author

Bayesian Information Criterion (BIC) — bic

<dl>

<dt>x</dt>
<dd>An object for which the log-likelihood of the DMM can be computed.</dd>


<dt>sequences</dt>
<dd>A list of vectors representing the sequences for which the BIC will be computed based on <code>x</code>.</dd>


<dt>ncpu</dt>
<dd>Default=2. Represents the number of cores used to parallelized computation. If ncpu=-1, then it uses all available cores.</dd>

</dl>

bic: Bayesian Information Criterion (BIC)

Description

Usage

Value

Arguments

Author

References