covidrisk: covidrisk Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

covidrisk Bayesian Network

Description

Highly efficient structural learning of sparse staged trees.

Format

A discrete Bayesian network to to investigate how various country risks and risks associated to the COVID-19 epidemics relate to each other. The Bayesian network is learned as in the referenced paper. The vertices are:

HAZARD

(low, high);

VULNERABILITY

(low, high);

COPING

(low, high);

RISK

(low, high);

ECONOMIC

(low, high);

BUSINESS

(low, high);

POLITICAL

(low, high);

COMMERCIAL

(low, high);

FINANCING

(low, high);

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

References

Leonelli, M., & Varando, G. (2022, September). Highly efficient structural learning of sparse staged trees. In International Conference on Probabilistic Graphical Models (pp. 193-204). PMLR.

bnRep documentation built on April 12, 2025, 1:13 a.m.