R/BayesPostEst-package.R

In BayesPostEst: Generate Postestimation Quantities for Bayesian MCMC Estimation

#' BayesPostEst Overview
#'
#' This package currently has nine main functions that can be used to generate 
#' and plot postestimation quantities after estimating Bayesian regression models using MCMC. 
#' The package combines functions written originally for Johannes Karreth's workshop on 
#' Bayesian modeling at the ICPSR Summer program. Currently BayesPostEst focuses mostly on 
#' generalized linear regression models for binary outcomes (logistic and probit regression). 
#' The vignette for this package has a walk-through of each function in action. 
#' Please refer to that to get an overview of all the functions, or visit the 
#' documentation for a specific function of your choice. Johannes Karreth's website
#' (http://www.jkarreth.net) also has resources for getting started with Bayesian 
#' analysis, fitting models, and presenting results.
#'
#' @section Main Functions:
#' \itemize{
#' \item \code{mcmcAveProb()}
#' \item \code{mcmcObsProb()}
#' \item \code{mcmcFD()}
#' \item \code{mcmcMargEff()}
#' \item \code{mcmcRocPrc()}
#' \item \code{mcmcRocPrcGen()}
#' \item \code{mcmcTab()}
#' \item \code{mcmcReg()}
#' \item \code{plot.mcmcFD()}
#' }
#'
#' @name BayesPostEst
#' @docType package
"_PACKAGE"