filter_same_cycle

Given an id variable that labels the different instances of a time series
inside a dataset, discard the rows that have values from more than 1 id.

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

filter_same_cycle function

<dl><dt>f_dt</dt>
<dd>folded data.table</dd>
<dt>size</dt>
<dd>the size of the data.table</dd>
<dt>id_var</dt>
<dd>the variable that labels each individual instance of the time series</dd></dl>

Arguments

Filter the instances in a data.table with different ids in each row — filter_same_cycle

<dl>

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


<dt>size</dt>
<dd>the size of the data.table</dd>


<dt>id_var</dt>
<dd>the variable that labels each individual instance of the time series</dd>

</dl>

filter_same_cycle: Filter the instances in a data.table with different ids in each row

Description

Usage

Value

Arguments

Examples