An Introduction to R and bayesm
Peter E. Rossi, Greg M. Allenby, Sanjog Misra · 2024
An Introduction to R and bayesmIn order to facilitate computation of the models in this book, we created a set of programs written in R and C++.R is a general purpose programming and statistical analysis system.R is free and available on the web.We have made our suite of programs into what is called an R "package."Our package is named bayesm.This package is easy to download and install from within R and is thoroughly documented, including test examples and illustrative datasets.This appendix provides an introduction to the R environment and bayesm.In addition, there are many excellent books and video tutorials available on the R environment and RStudio enhancements. A.1 SETTING UP THE R ENVIRONMENT AND BAYESMVirtually, all users of the R statistical language use the RStudio Integrated Development environment (IDE).RStudio works on top of R and provides a convenient visual and programming interface.Of particular interest is that RStudio provides a graphical interface that makes R programming and package installation very convenient.RStudio provides a very nice code development environment, which includes dynamic syntax checking of R code and integration of the interface with C++.RStudio also supports a very wide variety of enhancements to the basic R interface including dynamic report generation using Rmarkdown. A.1.1 Obtaining RVisit http://cran.r-project.org/ or google "R language."CRAN is a network of mirror sites that allow you to download precompiled binary versions of R or source.There are pre-compiled versions of R for both Linux, Windows and MacOS.Download the appropriate version and install on your computer.We recommend a minimum of 16GB of memory for small to moderate sized datasets and MCMC inference. Bayesian Statistics and Marketing, Second Edition.