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BayesPostEst  

Generate Postestimation Quantities for Bayesian MCMC Estimation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesPostEst", "0.4.1")



Attach the package and use:
library("BayesPostEst")
Maintained by
Shana Scogin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-05
Latest Update: 2021-11-11
Description:
An implementation of functions to generate and plot postestimation quantities after estimating Bayesian regression models using Markov chain Monte Carlo (MCMC). Functionality includes the estimation of the Precision-Recall curves (see Beger, 2016 ), the implementation of the observed values method of calculating predicted probabilities by Hanmer and Kalkan (2013) , the implementation of the average value method of calculating predicted probabilities (see King, Tomz, and Wittenberg, 2000 ), and the generation and plotting of first differences to summarize typical effects across covariates (see Long 1997, ISBN:9780803973749; King, Tomz, and Wittenberg, 2000 ). This package can be used with MCMC output generated by any Bayesian estimation tool including 'JAGS', 'BUGS', 'MCMCpack', and 'Stan'.
How to cite:
Shana Scogin (2019). BayesPostEst: Generate Postestimation Quantities for Bayesian MCMC Estimation. R package version 0.4.1, https://cran.r-project.org/web/packages/BayesPostEst. Accessed 27 Oct. 2026.
Previous versions and publish date:
0.0.1 (2019-08-05 14:20), 0.1.0 (2019-10-06 06:10), 0.2.0 (2019-12-15 00:10), 0.2.1 (2020-05-29 01:50), 0.3.1 (2021-01-09 01:20), 0.3.2 (2021-11-11 09:10), 0.4.0 (2025-08-18 22:20), (2026-09-27 04:40)
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Complete documentation for BayesPostEst
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