Work

Additive Bayesian Networks

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.

Source: The Journal of Open Source Software

DOI: 10.21105/joss.06822

Authors: Matteo Delucchi, Jonas I. Liechti, Georg R. Spinner, Reinhard Furrer

Institutions: T4D GmbH (Switzerland), ZHAW Zurich University of Applied Sciences, University of Zurich

Language: English

Topic: Bayesian Modeling and Causal Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Zürcher Hochschule für Angewandte Wissenschaften

OpenAlex ID: W4402974409