bridgesampling: An R Package for Estimating Normalizing Constants
Dublin Core
Title
bridgesampling: An R Package for Estimating Normalizing Constants
Subject
bridge sampling, marginal likelihood, model selection, Bayes factor, Warp-III
Description
Statistical procedures such as Bayes factor model selection and Bayesian model averaging require the computation of normalizing constants (e.g., marginal likelihoods). These
normalizing constants are notoriously difficult to obtain, as they usually involve highdimensional integrals that cannot be solved analytically. Here we introduce an R package
that uses bridge sampling (Meng and Wong 1996; Meng and Schilling 2002) to estimate
normalizing constants in a generic and easy-to-use fashion. For models implemented in
Stan, the estimation procedure is automatic. We illustrate the functionality of the package
with three examples.
normalizing constants are notoriously difficult to obtain, as they usually involve highdimensional integrals that cannot be solved analytically. Here we introduce an R package
that uses bridge sampling (Meng and Wong 1996; Meng and Schilling 2002) to estimate
normalizing constants in a generic and easy-to-use fashion. For models implemented in
Stan, the estimation procedure is automatic. We illustrate the functionality of the package
with three examples.
Creator
Quentin F. Gronau
Source
https://www.jstatsoft.org/article/view/v092i10
Publisher
University of Amsterdam
Date
February 2020
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Quentin F. Gronau, “bridgesampling: An R Package for Estimating Normalizing Constants,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8114.