BayesGOF: Bayesian Modeling via Goodness of Fit

Non-parametric method for learning prior distribution starting with parametric (subjective) prior. It performs four interconnected tasks: (i) characterizes the uncertainty of the elicited prior; (ii) exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) performs macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. (2017, Technical Report).

Version: 1.3
Depends: orthopolynom, VGAM
Published: 2017-11-16
Author: Subhadeep Mukhopadhyay, Douglas Fletcher
Maintainer: Doug Fletcher <tug25070 at>
License: GPL-2
NeedsCompilation: no
CRAN checks: BayesGOF results


Reference manual: BayesGOF.pdf
Package source: BayesGOF_1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: BayesGOF_1.3.tgz
OS X Mavericks binaries: r-oldrel: BayesGOF_1.3.tgz


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