Generate Postestimation Quantities for Bayesian MCMC Estimation
Deprecated functions in package BayesPostEst.
BayesPostEst Overview
Compute ROC and PR curve points
Try to identify link function
Try to identify if a stanfit model is a binary choice model
Predicted Probabilities using Bayesian MCMC estimates for the "Average...
Coefficient Plots for MCMC Output
First Differences of a Bayesian Logit or Probit model
Marginal Effects Plots for MCMC Output
Predicted Probabilities using Bayesian MCMC estimates for the Average ...
LaTeX or HTML regression tables for MCMC Output
ROC and Precision-Recall Curves using Bayesian MCMC estimates
ROC and Precision-Recall Curves using Bayesian MCMC estimates generali...
Summarize Bayesian MCMC OutputR function for summarizing MCMC output i...
Constructor for mcmcRocPrc objects
Plot Method for First Differences from MCMC output
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 <doi:10.2139/ssrn.2765419>), the implementation of the observed values method of calculating predicted probabilities by Hanmer and Kalkan (2013) <doi:10.1111/j.1540-5907.2012.00602.x>, the implementation of the average value method of calculating predicted probabilities (see King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>), and the generation and plotting of first differences to summarize typical effects across covariates (see Long 1997, ISBN:9780803973749; King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>). This package can be used with MCMC output generated by any Bayesian estimation tool including 'JAGS', 'BUGS', 'MCMCpack', and 'Stan'.
Useful links