BayesPostEst is an R package with convenience functions to generate and present quantities of interest after estimating Bayesian regression models fit using MCMC. Quantities of interest include predicted probabilities and changes in probabilities in generalized linear models and analyses of model fit using ROC curves and precision-recall curves. The package also contains two functions to create publication-ready tables summarizing model results with an assessment of substantively meaningful effect sizes.This is an archive for a paper published in the Journal of Open Source Software to accompany this version of the R package BayesPostEst
Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The exi...
The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian set...
This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression mode...
This R package provides post-processing tools for MCMC samples of partitions to summarize the poster...
We introduce MCMCpack, an R package that contains functions to perform Bayesian inference using post...
International audienceThis Bayesian modeling book provides a self-contained entry to computational B...
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Fo...
This article describes the BMS (Bayesian model sampling) package for R that implements Bayesian mode...
We describe bayesPop, an R package for producing probabilistic population projections for all countr...
The exponential growth of social data both in volume and complexity has increasingly exposed many of...
Abstract BayesMallows is an R package for analyzing preference data in the form of rankings with the...
We introduce MCMCpack, an R package that contains functions to perform Bayesian inference using pos...
Description Bayesian Model Averaging for linear models with a wide choice of (customizable) pri-ors....
This R package provides post-processing tools for MCMC samples of partitions to summarize the poster...
The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian set...
Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The exi...
The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian set...
This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression mode...
This R package provides post-processing tools for MCMC samples of partitions to summarize the poster...
We introduce MCMCpack, an R package that contains functions to perform Bayesian inference using post...
International audienceThis Bayesian modeling book provides a self-contained entry to computational B...
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Fo...
This article describes the BMS (Bayesian model sampling) package for R that implements Bayesian mode...
We describe bayesPop, an R package for producing probabilistic population projections for all countr...
The exponential growth of social data both in volume and complexity has increasingly exposed many of...
Abstract BayesMallows is an R package for analyzing preference data in the form of rankings with the...
We introduce MCMCpack, an R package that contains functions to perform Bayesian inference using pos...
Description Bayesian Model Averaging for linear models with a wide choice of (customizable) pri-ors....
This R package provides post-processing tools for MCMC samples of partitions to summarize the poster...
The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian set...
Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The exi...
The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian set...
This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression mode...