knitr: Elegant, flexible and fast dynamic report generation with R

The knitr package was designed to be a transparent engine for dynamic report generation with R, solve some long-standing problems in Sweave, and combine features in other add-on packages into one package.

http://yihui.name/knitr/


Posted by Kusal Rathnayake

The Copula

To get an idea about modelling by means of copula, follow this link which contains presentations, videos and related R codes

https://sites.google.com/a/wisc.edu/jed-frees/multivariate-regression-using-copulas

Through this introductory material and examples, I hope you can understand how to use copulas in their own fields of applications.

The R Markdown Cheat Sheet

This link provides a  quick reference guide for writing reports with R Markdown.
http://shiny.rstudio.com/articles/rm-cheatsheet.html

Posted by Shanika Basnayake

Use R for Fun!

This package is a collection of some classical computer games (e.g. the Mine sweeper and Five in a row) as well as other funny stuff.

Some examples:

## install.packages('fun')
library(fun)
if (.Platform$OS.type == "windows") x11() else x11(type = "Xlib")
mine_sweeper()

library(fun)
gomoku()

You can take a look at the list of functions in this package by reading the HTML help page (go to help.start()), and I also need to mention the demos, e.g. see demo('TurtleGraphics') for a demo of Turtle graphics (how many people know the old Logo programming language?), and demo(package = 'fun') for a list of all demos in this package.

 

demo('RealTurtle', package = 'fun')

 

 

Posted by Wathsala Karunarathna

 

 

R plots and graph gallery

R has great graphics and plotting capabilities and can produce a wide range of plots very easily. The following is an R plot gallery with a selection of different R plot types and graphs that were all generated with R. In each case you can click on the graph to see the commented code that produced the plot in R. Note that the R code produces pdf files, which I have converted in gimp to png format for displaying on the web.

http://www.sr.bham.ac.uk/~ajrs/R/r-gallery.html

 

Posted by Nathasha Wijesinghe

 

 

 

 

Getting Started with R

There are hundreds of websites that can help you learn the language. Here's how you can use some of the best to become a productive R programmer.

• Start by downloading R and RStudio.

• Learn the basics: Visit Try R to learn how to write basic R code. These interactive lessons will get you writing real code in minutes, and they'll tell you immediately when you go wrong.

• Broaden your skills: Work through The Beginner's Guide to R by Computerworld Magazine. This 30 page guide will show you how to install R, load data, run analyses, make graphs, and more.

• Practice good habits: Read the R Style Guide for advice on how to write readable, maintainable code. This is how other R users will expect your code to look when you share it.

• Look up help: When you need to learn more about an R function or package, visit Rdocumentation.org, a searchable database of R documentation. You can search for R packages and functions, look at package download statistics, and leave and read comments about R functions.

• Ask questions: Seek help at StackOverflow, a searchable forum of questions and answers about computer programming. StackOverflow has answered (and archived) over 40,000 questions related to R programming. You can browse StackOverflow's archives and see which answers have been up voted by users, or you can ask your own R related questions and wait for a response.
• If you a have question that is more about statistical methodology there are also plenty of R users active on the the  CrossValidated Q&A community.

• Keep tabs on the R community: Read R bloggers, a blog aggregator that reposts R related articles from across the web. A good place to find R tutorials, announcements, and other random happenings.

• Deepen your expertise: Once you've gained some familiarity with R, Advanced R provides an entertaining roadmap to some of the deeper subtleties of the language and how to work with it most effectively.

https://support.rstudio.com/hc/en-us/articles/201141096-Getting-Started-with-R



Posted by Shenali Wijesinghe

R Markdown — Dynamic Documents for R

R Markdown is an authoring format that enables easy creation of dynamic documents, presentations, and reports from R. It combines the core syntax of markdown (an easy-to-write plain text format) with embedded R code chunks that are run so their output can be included in the final document. R Markdown documents are fully reproducible (they can be automatically regenerated whenever underlying R code or data changes).

For more information

http://rmarkdown.rstudio.com/

Posted by Mohamed Abraj