Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences.nbsp; Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years.nbsp; In recent years many of these software developments have taken place within the R community, either in the form of new packages or by providing an R interface to existing software.nbsp; This book attempts to give the reader a gentle introduction to graphical modeling using R and the main features of some of these packages.nbsp; In addition, the booknbsp;provides examples of how more advanced aspects of graphical modeling can be represented and handled within R.nbsp; Topics covered in the seven chapters include graphical models for contingency tables, Gaussian and mixed graphical models, Bayesian networks and modeling high dimensional data.