fit_dbn_params

Fits the parameters of the DBN via MLE. The "mu" vector of means 
and the "sigma" covariance matrix are set as attributes of the dbn.fit 
object for future exact inference.

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

fit_dbn_params function

<dl><dt>net</dt>
<dd>the structure of the DBN</dd>
<dt>f_dt</dt>
<dd>a folded data.table</dd>
<dt>...</dt>
<dd>additional parameters for the <code>bn.fit</code> function</dd></dl>

Arguments

Fits a markovian n DBN model — fit_dbn_params

<dl>

<dt>net</dt>
<dd>the structure of the DBN</dd>


<dt>f_dt</dt>
<dd>a folded data.table</dd>


<dt>...</dt>
<dd>additional parameters for the <code>bn.fit</code> function</dd>

</dl>

fit_dbn_params: Fits a markovian n DBN model

Description

Usage

Value

Arguments

Examples