bnRep_summary

Summary of the Bayesian networks in <code>bnRep</code> reporting various graph, definition and application details.

datasets

A collection of Bayesian networks (discrete, Gaussian, and conditional linear Gaussian) collated from recent academic literature. The 'bnRep_summary' object provides an overview of the Bayesian networks in the repository and the package documentation includes details about the variables in each network. A Shiny app to explore the repository can be launched with 'bnRep_app()' and is available online at <https://manueleleonelli.shinyapps.io/bnRep>. Reference: 'M. Leonelli' (2025) <doi:10.1016/j.neucom.2025.129502>.

Manuele Leonelli

bnRep

A Repository of Bayesian Networks from the Academic Literature

bnRep_summary function

A data frame with a row for each BN in <code>bnRep</code> and the following columns:<dl>
<dt>Name</dt>
<dd>Name of the R object storing the BN;</dd><dt>Type</dt>
<dd>Type of Bayesian network (Discrete, Gaussian, Hybrid);</dd><dt>Structure</dt>
<dd>How the graph of the BN was defined (Data, Expert, Fixed, Knowledge, Mixed, Synthetic);</dd><dt>Probabilities</dt>
<dd>How the probabilities of the BN were defined (Data, Expert, Knowledge, Mixed, Synthetic);</dd><dt>Graph</dt>
<dd>Type of graph of the BN (Generic, K-Dep, Naive Bayes, Reverse Naive Bayes, Reverse Tree, TAN, Tree);</dd><dt>Area</dt>
<dd>Subject area of the Bayesian network using the SJR classification (Agricultural Sciences, Business, Chemical Engineering, etc.);</dd><dt>Nodes</dt>
<dd>Number of nodes in the BN;</dd><dt>Arcs</dt>
<dd>Number of arcs in the BN;</dd><dt>Parameters</dt>
<dd>Number of free parameters in the BN;</dd><dt>Avg. Parents</dt>
<dd>Average number of parents;</dd><dt>Max Parents</dt>
<dd>Maximum number of parents;</dd><dt>Avg. Levels</dt>
<dd>Average number of discrete variables' levels;</dd><dt>Max Levels</dt>
<dd>Max number of discrete variables' levels;</dd><dt>Average Markov Blanket</dt>
<dd>Average size of a node's Markov blanket;</dd><dt>Year</dt>
<dd>Year of the publication where the BN appeared;</dd><dt>Journal</dt>
<dd>Journal where the BN appeared;</dd><dt>Reference</dt>
<dd>Reference of the paper where the BN appeared.</dd>
</dl>

Format

BnRep Summary — bnRep_summary

A data frame with a row for each BN in <code>bnRep</code> and the following columns:<dl>
<dt>Name</dt>
<dd>Name of the R object storing the BN;</dd>

<dt>Type</dt>
<dd>Type of Bayesian network (Discrete, Gaussian, Hybrid);</dd>

<dt>Structure</dt>
<dd>How the graph of the BN was defined (Data, Expert, Fixed, Knowledge, Mixed, Synthetic);</dd>

<dt>Probabilities</dt>
<dd>How the probabilities of the BN were defined (Data, Expert, Knowledge, Mixed, Synthetic);</dd>

<dt>Graph</dt>
<dd>Type of graph of the BN (Generic, K-Dep, Naive Bayes, Reverse Naive Bayes, Reverse Tree, TAN, Tree);</dd>

<dt>Area</dt>
<dd>Subject area of the Bayesian network using the SJR classification (Agricultural Sciences, Business, Chemical Engineering, etc.);</dd>

<dt>Nodes</dt>
<dd>Number of nodes in the BN;</dd>

<dt>Arcs</dt>
<dd>Number of arcs in the BN;</dd>

<dt>Parameters</dt>
<dd>Number of free parameters in the BN;</dd>

<dt>Avg. Parents</dt>
<dd>Average number of parents;</dd>

<dt>Max Parents</dt>
<dd>Maximum number of parents;</dd>

<dt>Avg. Levels</dt>
<dd>Average number of discrete variables' levels;</dd>

<dt>Max Levels</dt>
<dd>Max number of discrete variables' levels;</dd>

<dt>Average Markov Blanket</dt>
<dd>Average size of a node's Markov blanket;</dd>

<dt>Year</dt>
<dd>Year of the publication where the BN appeared;</dd>

<dt>Journal</dt>
<dd>Journal where the BN appeared;</dd>

<dt>Reference</dt>
<dd>Reference of the paper where the BN appeared.</dd>


</dl>

bnRep_summary: BnRep Summary

Description

Usage

Arguments

Format

Examples