Rcmdr Plug-in(s)

November 15, 2016
By

(This article was first published on Krishna's R Blog, and kindly contributed to R-bloggers)

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

 

To leave a comment for the author, please follow the link and comment on their blog: Krishna's R Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)