predict_bn

Performs inference over a Gaussian BN. It's thought to be used in a map for
a data.table, to use as evidence each separate row. If not specifically
needed, it's recommended to use the function <code>predict_dt</code> instead.
This function is deprecated and will be removed in a future version.

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

predict_bn function

<dl><dt>fit</dt>
<dd>the fitted bn</dd>
<dt>evidence</dt>
<dd>values of the variables used as evidence for the net</dd></dl>

Arguments

Performs inference over a fitted GBN — predict_bn

<dl>

<dt>fit</dt>
<dd>the fitted bn</dd>


<dt>evidence</dt>
<dd>values of the variables used as evidence for the net</dd>

</dl>

predict_bn: Performs inference over a fitted GBN

Description

Usage

Value

Arguments

Examples