create_causlist_cpp

Create a causal list from a DBN. This is the C++ backend of the function.

internal

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

create_causlist_cpp function

<dl><dt>cl</dt>
<dd>an initialized causality list</dd>
<dt>net</dt>
<dd>a dbn object treated as a list of lists</dd>
<dt>size</dt>
<dd>the size of the DBN</dd>
<dt>ordering</dt>
<dd>a list with the order of the variables in t_0</dd></dl>

Arguments

Create a causal list from a DBN. This is the C++ backend of the function. — create_causlist_cpp

<dl>

<dt>cl</dt>
<dd>an initialized causality list</dd>


<dt>net</dt>
<dd>a dbn object treated as a list of lists</dd>


<dt>size</dt>
<dd>the size of the DBN</dd>


<dt>ordering</dt>
<dd>a list with the order of the variables in t_0</dd>

</dl>

create_causlist_cpp: Create a causal list from a DBN. This is the C++ backend of the function.

Description

Usage

Value

Arguments