R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R’s popularity has increased substantially in recent years.

R is a GNU package. The source code for the R software environment is written primarily in C, Fortran, and R. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems. While R has a command line interface, there are several graphical front-ends available.


R open

Reproducible research

Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. In the more narrow context of data science…

Docker, JavaScript and R

Docker is this wonderful new way to play around with appliances without hurting your machine or stealing away heaps of time.

Pearson p-value

Numerical algorithms and statistical theory is quite robust and universal, but once you look into the various software implementations you discover that presumed standards are not so universal.

Time series analysis functions to remember

Diverse R functions related to timeseries analysis.
Twitter collage.

Some new R delights

CRAN contains heaps of packages but obviously there are even more goodies on GitHub.

R6 classes

Object oriented programming in R is possible but is hardly advertized and there is also the fact that there is a proliferation of ways to do OO in R.

iGraph analysis

Some concrete analysis of real-world graphs using iGraph.