Package: BayesGOF 5.2

Doug Fletcher

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 >).

Authors:Subhadeep Mukhopadhyay, Douglas Fletcher

BayesGOF_5.2.tar.gz
BayesGOF_5.2.tar.gz(r-4.7-any)BayesGOF_5.2.tar.gz(r-4.6-any)
BayesGOF_5.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BayesGOF/json (API)

# Install 'BayesGOF' in R:

install.packages('BayesGOF', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

arsenic - Arsenic levels in oyster tissue
AutoIns - Number of claims on an insurance policy
ChildIll - Frequency of child illness
CorbBfly - Corbet's Butterfly data
galaxy - Galaxy Data
NorbergIns - Norberg life insurance data
rat - Rat Tumor Data
ship - Portsmouth Navy Shipyard Data
steroid - Nasal Steroid Data
surg - Intestinal surgery data
tacks - Rolling Tacks Data
terb - Terbinafine trial data
ulcer - Recurrent Bleeding of Ulcers

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.62 score 1 packages 14 scripts 102 downloads 1 mentions 41 exports 5 dependencies

Last updated from:add399975c. Checks:2 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	148
source / vignettes	OK	299
linux-release-x86_64	NOTE	141
wasm-release	OK	120

Exports:DS.entropy DS.Finite.Bayes DS.macro.inf DS.macro.inf.bbu DS.macro.inf.nnu DS.macro.inf.pge DS.macro.inf.pgu DS.micro.inf DS.micro.inf.bbu DS.micro.inf.nnu DS.micro.inf.pge DS.micro.inf.pgu DS.posterior.reduce DS.prior DS.prior.bbu DS.prior.nnu DS.prior.pgu DS.sampler DS.sampler.post EXP.score gLP.basis gMLE.bb gMLE.nn gMLE.pg Local.Mode LP.smooth maxent.LP.par maxent.obj.convert plot.DS_FB_obj plot.DS_GF plot.DS_GF_macro_mean plot.DS_GF_macro_mode plot.DS_GF_micro print.DS_FB_obj print.DS_GF print.DS_GF_macro_mean print.DS_GF_macro_mode print.DS_GF_micro Reduce.LP.coef.univ rPPD.ds weight.fun.univ

Dependencies:Bolstad2 nleqslv orthopolynom polynom VGAM

Bayesian Modeling via Frequentist Goodness-of-Fit

I. Illustration using rat tumor data (Binomial Family) | Pre-Inferential Modeling | MacroInference | MicroInference | Finite Bayes | II. Comparison of $\mathcal{L}^2$ and maximum entropy representations using galaxy data (Normal Family) | III. Illustration using arsenic data (Normal Family) | IV. Illustration using child illness data (Poisson Family)

Rendered fromvignette_BayesGOF.Rmdusingknitr::rmarkdown

Last update: 2018-10-09
Started: 2018-01-05

Help page	Topics
Bayesian Modeling via Frequentist Goodness-of-Fit	BayesGOF-package BayesGOF
Arsenic levels in oyster tissue	arsenic
Number of claims on an insurance policy	AutoIns
Frequency of child illness	ChildIll
Corbet's Butterfly data	CorbBfly
Full and Excess Entropy of DS(G,m) prior	DS.entropy
Conduct Finite Bayes Inference on a DS object	DS.Finite.Bayes plot.DS_FB_obj print.DS_FB_obj
Execute MacroInference (mean or mode) on a DS object	DS.GF.macro.obj DS.macro.inf DS.macro.inf.bbu DS.macro.inf.nnu DS.macro.inf.pge DS.macro.inf.pgu Local.Mode plot.DS_GF_macro_mean plot.DS_GF_macro_mode print.DS_GF_macro_mean print.DS_GF_macro_mode
MicroInference for DS Prior Objects	DS.GF.micro.obj DS.micro.inf DS.micro.inf.bbu DS.micro.inf.nnu DS.micro.inf.pge DS.micro.inf.pgu plot.DS_GF_micro print.DS_GF_micro
Posterior Expectation and Modes of DS object	DS.posterior.reduce
Prior Diagnostics and Estimation	DS.GF.obj DS.prior DS.prior.bbu DS.prior.nnu DS.prior.pgu EXP.score LP.smooth maxent.LP.par maxent.obj.convert plot.DS_GF print.DS_GF Reduce.LP.coef.univ weight.fun.univ
Samples data from DS(G,m) distribution.	DS.sampler DS.sampler.post rPPD.ds
Galaxy Data	galaxy
Determine LP basis functions for prior distribution g	gLP.basis
Beta-Binomial Parameter Estimation	gMLE.bb mom.est
Normal-Normal Parameter Estimation	gMLE.nn
Negative-Binomial Parameter Estimation	gMLE.pg
Norberg life insurance data	NorbergIns
Rat Tumor Data	rat
Portsmouth Navy Shipyard Data	ship
Nasal Steroid Data	steroid
Intestinal surgery data	surg
Rolling Tacks Data	tacks
Terbinafine trial data	terb
Recurrent Bleeding of Ulcers	ulcer

Package: BayesGOF 5.2

BayesGOF: Bayesian Modeling via Frequentist Goodness-of-Fit

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)