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