Quantum Bayesian Networks

September 6, 2009

Addicted to R

Filed under: Uncategorized — rrtucci @ 5:48 pm

category: software feast!

There is an excellent website called Addicted to R, kept by Romain François. This blog post has the same title as his website, because I find it a funny title that coveys the strong enthusiasm of the R community.

What is R? R is a computer language and environment for doing calculations in Mathematical Statistics and plotting.

R is GNU licensed software, and is available for every platform under the sun at the CRAN website (CRAN is an acronym for Comprehensive R Archive Network, in analogy to CTAN for TeX users).

R can be run via the command line or through programs stored in script files.

R provides a lot of handy system functions. In addition, a large number of special purpose packages have been written for R by the R community. These may be found at the CRAN website, listed alphabetically under “Packages”, or thematically, under “Task Views” (if that is not enough for you, try their search engine). These packages are called CRANberries by some in the R community. 🙂

Whether you are a frequentist or a Bayesian or both, you will love R.

Bayesian Connection. Most modern courses in Bayesian Statistics (or at least the ones I like best), supplement the theory with some instruction in the use of WinBugs and R. For example, take a look at the syllabus of this university course (by Prof. David Madigan at Rutgers U.), and how about this blog written by a professor teaching a course in B. Statistics (Prof. Jim Albert at Bowling Green State U.). Don’t miss Albert’s classic post. “Do graduate students prefer McDonalds?”

The CRAN website has a Task View called “Bayesian Inference” that is of special interest to Bayesian Network and MCMC (Markov Chain Monte Carlo) aficionados like me. Note that there are some tools linking WinBugs and R.

Learning R. There are numerous quick R tutorials on the internet. Find one that suits your taste. For example, here is one.

The CRAN website also provides some fine documentation, under “Manuals”. For example, check out their “Introduction to R”.

You can even test run R without downloading it. This webpage links to web interfaces for both R and Octave.

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