Publication: Additive Bayesian Network Modeling with the R Package abn
Additive Bayesian Network Modeling with the R Package abn
Date
Date
Date
Citations
Kratzer, G., Lewis, F., Comin, A., Pittavino, M., & Furrer, R. (2023). Additive Bayesian Network Modeling with the R Package abn. Journal of Statistical Software, 105(8), online. https://doi.org/10.18637/jss.v105.i08
Abstract
Abstract
Abstract
The R package abn is designed to fit additive Bayesian models to observational datasets. It 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. It supports a possible blend of continuous, discrete and count data 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
Metrics
Downloads
Views
Additional indexing
Creators (Authors)
- Kratzer, Gilles
- Lewis, Fraser
- Comin, Arianna
- Pittavino, Marta
Volume
Volume
Volume
Number
Number
Number
Page range/Item number
Page range/Item number
Page range/Item number
Item Type
Item Type
Item Type
Keywords
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
OA Status
OA Status
OA Status
Free Access at
Free Access at
Free Access at
Publisher DOI
Metrics
Downloads
Views
Citations
Kratzer, G., Lewis, F., Comin, A., Pittavino, M., & Furrer, R. (2023). Additive Bayesian Network Modeling with the R Package abn. Journal of Statistical Software, 105(8), online. https://doi.org/10.18637/jss.v105.i08
