calc_sigma

Given a "bn.fit" or a "dbn.fit" object, calculate the sigma covariance 
matrix of the equivalent multivariate Gaussian distribution. 
Front end of a C++ function.

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

calc_sigma function

<dl><dt>fit</dt>
<dd>a bn.fit or dbn.fit object</dd></dl>

Arguments

Calculate the sigma covariance matrix from a fitted BN or DBN — calc_sigma

<dl>

<dt>fit</dt>
<dd>a bn.fit or dbn.fit object</dd>

</dl>

calc_sigma: Calculate the sigma covariance matrix from a fitted BN or DBN

Description

Usage

Value

Arguments

Examples