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If you're looking for just the right package to solve your R problem, you could always browse through the list of available packages on CRAN. But with almost 6000 entries, that's not going to be the most efficient process.

A statistical consultant known only as "Stanford PhD" has put together a table comparing the statistical capabilities of the software packages R, Matlab, SAS, Stata and SPSS. For each of 57 methods (including techniques like "ridge regression", "survival analysis", "optimization") the author ranks the capabilities of each software package as "Yes" (fully supported), "Limited" or "Experimental". Here are the first few rows of the table:

Joe wrote about this already, but now the recording of John Chambers' keynote presentation from the useR! 2014 conference, Interfaces, Efficiency and Big Data, is now available for viewing thanks to Data Science LA.

David Smith's picture
August 8, 2014

Earlier this summer I got to try my first hedge maze in an English country garden, during the open day at Chevening House in Kent. I thought I was pretty good at mazes (on paper, at least), but what I thought was going to be a 5-minute stroll turned into almost an hour of fun turning to desperation. 

So says, in a recent article 11 Market Trends in Advanced Analytics.

R, an open source programming language for computational statistics, visualization and data is becoming a ubiquitous tool in advanced analytics offerings.

In case you missed them, here are some articles from July of particular interest to R users:  

The deadline for our contest to visualize the location of R user groups has been extended to August 16.

Previews of R-related sessions at this year's JSM conference in Boston.

Using package repositories to
recreate the past, distribute the present, and protect against the future

by Gabriel Becker (@groundwalkergmb)
Bioinformatics and Computational Biology
Genentech Research and Early Development