Bayesian Modeling via Frequentist Goodness-of-Fit
tools:::Rd_package_title("BayesGOF")
Full and Excess Entropy of DS(G,m) prior
Conduct Finite Bayes Inference on a DS object
Execute MacroInference (mean or mode) on a DS object
MicroInference for DS Prior Objects
Posterior Expectation and Modes of DS object
Prior Diagnostics and Estimation
Samples data from DS(G,m) distribution.
Determine LP basis functions for prior distribution
Beta-Binomial Parameter Estimation
Normal-Normal Parameter Estimation
Negative-Binomial Parameter Estimation
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 >).