argument

Towards an empirically informed normative Bayesian scheme-based account of argument from expert opinion.

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

argument function

A discrete Bayesian network formalizing Walton's re-constructed set of critical questions. Probabilities were given within the referenced paper. The vertices are:<dl>
<dt>DecisionProcess</dt>
<dd>(Not based on evidence, Integrative complexity, Absence of integrative complexity);</dd><dt>DeliberativePractice</dt>
<dd>(FALSE, TRUE);</dd><dt>ExpertAssertsHypothesis</dt>
<dd>(FALSE, TRUE);</dd><dt>Feedback</dt>
<dd>(FALSE, TRUE);</dd><dt>GenuineExpertise</dt>
<dd>(FALSE, TRUE);</dd><dt>Hypothesis</dt>
<dd>(FALSE, TRUE);</dd><dt>ObjectiveEvidence</dt>
<dd>(FALSE, TRUE);</dd><dt>RegularPractice</dt>
<dd>(FALSE, TRUE);</dd><dt>Validity</dt>
<dd>(High, Medium, High);</dd><dt>WellInformedPractice</dt>
<dd>(FALSE, TRUE);</dd>
</dl>

argument: argument Bayesian Network

Description

Arguments

Value

Format

References