dmfletch/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 >).

Getting started

Package details

AuthorSubhadeep Mukhopadhyay, Douglas Fletcher
MaintainerDoug Fletcher <tug25070@temple.edu>
LicenseGPL-2
Version5.2
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("dmfletch/BayesGOF")
dmfletch/BayesGOF documentation built on Nov. 25, 2019, 12:35 a.m.