Additive Bayesian Network Modeling with the R Package abn

Additive Bayesian Network Modeling with the R Package abn

: structure learning, graphical models, greedy search, exact search, scoring algorithm, GLM, graph theory

The R package abn is designed to fit additive Bayesian network models to observational datasets and contains routines to score Bayesian networks based on Bayesian or
information theoretic formulations of generalized linear models. It is equipped with exact
search and greedy search algorithms to select the best network, and supports continuous,
discrete and count data in the same model and input of prior knowledge at a structural
level. The Bayesian implementation supports random effects to control for one-layer clustering. In this paper, we give an overview of the methodology and illustrate the package’s
functionality using a veterinary dataset concerned with respiratory diseases in commercial
swine production.

Gilles Kratzer

https://www.jstatsoft.org/article/view/v105i08

University of Zurich

January 2023

Fajar Bagus W

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