trajectories

Context-specific causal discovery for categorical data using staged trees.

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

trajectories function

A discrete Bayesian network modeling the trajectory of patients hospitalized due to COVID. The Bayesian network is learned as in the referenced paper. The vertices are:<dl>
<dt>SEX</dt>
<dd>(male, female);</dd><dt>ICU</dt>
<dd>(0, 1);</dd><dt>OUT</dt>
<dd>(death, survived);</dd><dt>AGE</dt>
<dd>(child, adult, elder);</dd><dt>RSP</dt>
<dd>(intub, mask, no);</dd>
</dl>

trajectories: trajectories Bayesian Network

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References