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BayesGOF  

Bayesian Modeling via Frequentist Goodness-of-Fit
View on CRAN: Click here


Download and install BayesGOF package within the R console
Install from CRAN:
install.packages("BayesGOF")

Install from Github:
library("remotes")
install_github("cran/BayesGOF")

Install by package version:
library("remotes")
install_version("BayesGOF", "5.2")



Attach the package and use:
library("BayesGOF")
Maintained by
Doug Fletcher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-16
Latest Update: 2018-10-09
Description:
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" ().
How to cite:
Doug Fletcher (2017). BayesGOF: Bayesian Modeling via Frequentist Goodness-of-Fit. R package version 5.2, https://cran.r-project.org/web/packages/BayesGOF. Accessed 03 Dec. 2024.
Previous versions and publish date:
1.3 (2017-11-16 11:20), 1.4 (2018-01-05 20:00), 2.1 (2018-02-08 18:23), 3.0 (2018-04-13 12:16), 4.0 (2018-05-18 05:12), 4.2 (2018-08-15 17:10), 5.0 (2018-10-04 06:20), 5.1 (2018-10-05 13:42)
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Complete documentation for BayesGOF
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