Additive Bayesian Networks
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.
Publication Details
- Journal
- Zurich Open Repository and Archive (University of Zurich)
- Published
- 2024-09-30
- DOI
- https://doi.org/10.5167/uzh-267366
- Primary Topic
- Bayesian Modeling and Causal Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00