These plug-ins enhance statistical graphical user interface by extending new menus to statistical package provided by Rcmdr. While the original GUI was created for a basic statistics calculations, enabling of extensions (or plug-ins) has greatly enhanced the possible use and scope of this software. Installing these plug-ins is quite easy. They can be installed like any other R package. After installing the plugin package, these plug-ins can be activated by simply selecting the menu option Tools – Load Rcmdr plug-in(s) option in Rcmdr. Some useful Rcmdr plug-ins and their usage are provided below :

1.RcmdrPlugin.bca – Business and Customer Analytics
2.RcmdrPlugin.depthTools – A package that implements different statistical tools for the description and analysis of gene expression data based on the concept of data depth
3.RcmdrPlugin.DoE – Design of Experiments
4.RcmdrPlugin.EBM – Evidence Based Medicine plug-in
5.RcmdrPlugin.epack – Plugin for Time Series
6. RcmdrPlugin.EZR : adds a variety of statistical functions, including survival analyses, ROC analyses, metaanalyses, sample size calculation, and so on
7.RcmdrPlugin.FactoMineR : dedicated to multivariate Data Analysis
8.RcmdrPlugin.KMggplor2 – Kaplan-Meier plots and other plots by using the ggplot2 package
9. RcmdrPlugin.NMBU – extends linear models and provides new extended interfaces for PCA,PLS,LDA,QDA, clustering of variables, tests, plots etc.
10. RcmdrPlugin.sampling – provides tools for calculating sample sizes and selecting samples using various sampling designs
11. Rcmdr.survival : survival package, with dialogs for Cox models, parametric survival regression models, estimation of survival curves etc.
12. Rcmdr.temis – provides an integrated solution to perform a series of text mining tasks