Year: 2024
Type: article
Abstract: The R package abn is a comprehensive tool for Bayesian Network (BN) analysis, a form of probabilistic graphical model. BNs are a type of statistical model that leverages the principles of Bayesian statistics and graph theory to provide a framework for representing complex multivariate data. They can derive a directed acyclic graph from empirical data to describe the dependency structure between random variables. Additive Bayesian Network (ABN) models extend the concept of generalized linear models, typically used for predicting a single outcome, to scenarios with multiple dependent variables (e.g., Kratzer et al. (2023)). This makes them a powerful tool for understanding complex, multivariate datasets. This package provides routines for structure learning and parameter estimation of ABN models.
DOI: 10.5167/uzh-267366
Authors: Delucchi, Matteo, Liechti, Jonas I, Spinner, Georg R, Furrer, Reinhard
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6967374464
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