BayesGOF: Bayesian Modeling via Frequentist Goodness-of-Fit

A Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized Empirical Bayes via Frequentist Goodness of Fit" (<>).

Version: 5.2
Depends: orthopolynom, VGAM, Bolstad2, nleqslv
Suggests: knitr, rmarkdown
Published: 2018-10-09
DOI: 10.32614/CRAN.package.BayesGOF
Author: Subhadeep Mukhopadhyay, Douglas Fletcher
Maintainer: Doug Fletcher <tug25070 at>
License: GPL-2
NeedsCompilation: no
In views: Bayesian
CRAN checks: BayesGOF results


Reference manual: BayesGOF.pdf
Vignettes: Bayesian Modeling via Frequentist Goodness-of-Fit


Package source: BayesGOF_5.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BayesGOF_5.2.tgz, r-oldrel (arm64): BayesGOF_5.2.tgz, r-release (x86_64): BayesGOF_5.2.tgz, r-oldrel (x86_64): BayesGOF_5.2.tgz
Old sources: BayesGOF archive

Reverse dependencies:

Reverse depends: LPRelevance


Please use the canonical form to link to this page.