rbn.dbn.fit

Generic method for "dbn.fit" S3 objects. 
Calls bnlearn's <code>rbn</code> underneath.

Learning and inference over dynamic Bayesian networks of arbitrary
Markovian order. Extends some of the functionality offered by the 'bnlearn'
package to learn the networks from data and perform exact inference.
It offers three structure learning algorithms for dynamic Bayesian networks:
Trabelsi G. (2013) <doi:10.1007/978-3-642-41398-8_34>, Santos F.P. and Maciel C.D. (2014)
<doi:10.1109/BRC.2014.6880957>, Quesada D., Bielza C. and Larrañaga P. (2021)
<doi:10.1007/978-3-030-86271-8_14>. It also offers the possibility to perform
forecasts of arbitrary length. A tool for visualizing the structure of the
net is also provided via the 'visNetwork' package.

David Quesada

dbnR

Dynamic Bayesian Network Learning and Inference

Gabriel Valverde

rbn.dbn.fit function

<dl><dt>x</dt>
<dd>the fitted network</dd>
<dt>n</dt>
<dd>number of samples</dd>
<dt>...</dt>
<dd>additional parameters</dd></dl>

Arguments

Simulates random samples from a fitted DBN — rbn.dbn.fit

<dl>

<dt>x</dt>
<dd>the fitted network</dd>


<dt>n</dt>
<dd>number of samples</dd>


<dt>...</dt>
<dd>additional parameters</dd>

</dl>

rbn.dbn.fit: Simulates random samples from a fitted DBN

Description

Usage

Value

Arguments