4.6 Article

bridgesampling: An R Package for Estimating Normalizing Constants

Journal

JOURNAL OF STATISTICAL SOFTWARE
Volume 92, Issue 10, Pages 1-29

Publisher

JOURNAL STATISTICAL SOFTWARE
DOI: 10.18637/jss.v092.i10

Keywords

bridge sampling; marginal likelihood; model selection; Bayes factor; Warp-III

Funding

  1. Netherlands Organisation for Scientific Research (NWO) [406.16.528]
  2. NWO Vici grant [016.Vici.170.083]
  3. Berkeley Initiative for Transparency in the Social Sciences, a program of the Center for Effective Global Action (CEGA)
  4. Laura and John Arnold Foundation

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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 high-dimensional 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.

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