vaccine

Sensitivity analysis in multilinear probabilistic models.

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

vaccine function

A (synthetic) discrete Bayesian network modeling a vaccine scenario. Probabilities were given within the referenced paper. The vertices are:<dl>
<dt>Screening_Test</dt>
<dd>(Negative, Positive);</dd><dt>Disease</dt>
<dd>(Healthy, Mildly, Severly);</dd><dt>Vaccine</dt>
<dd>(No, Yes);</dd>
</dl>@return An object of class <code>bn.fit</code>. Refer to the documentation of <code>bnlearn</code> for details.

Format

vaccine Bayesian Network — vaccine

A (synthetic) discrete Bayesian network modeling a vaccine scenario. Probabilities were given within the referenced paper. The vertices are:<dl>
<dt>Screening_Test</dt>
<dd>(Negative, Positive);</dd>

<dt>Disease</dt>
<dd>(Healthy, Mildly, Severly);</dd>

<dt>Vaccine</dt>
<dd>(No, Yes);</dd>


</dl>

@return An object of class <code>bn.fit</code>. Refer to the documentation of <code>bnlearn</code> for details.

vaccine: vaccine Bayesian Network

Description

Arguments

Format

References