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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" (<https://www.nature.com/articles/s41598-018-28130-5>).

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 temple.edu>
License:GPL-2
NeedsCompilation:no
In views:Bayesian
CRAN checks:BayesGOF results

Documentation:

Reference manual:BayesGOF.html ,BayesGOF.pdf
Vignettes:Bayesian Modeling via Frequentist Goodness-of-Fit (source,R code)

Downloads:

Package source: BayesGOF_5.2.tar.gz
Windows binaries: r-devel:BayesGOF_5.2.zip, r-release:BayesGOF_5.2.zip, r-oldrel:BayesGOF_5.2.zip
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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=BayesGOFto link to this page.


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