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by Andrie de Vries

Last week we announced the availability of Revolution R Open, an enhanced distribution of R.  One of the enhancements is the inclusion of high performance linear algebra libraries, specifically the Intel MKL. This library significantly speeds up many statistical calculations, e.g. the matrix algebra that forms the basis of many statistical algorithms.

by Jamie F Olson
Professional Services Consultant, Revolution Analytics

One challenge in transitioning R code into a production environment is ensuring consistency and reliability. These challenges span a wide variety of issues, but runtime characteristics are an important operational characteristic. Specifically, production code should have a consistent, predictable runtime for a particular computational infrastructure. Among other things, this makes it possible to plan and scale IT infrastructure based on operational requirements.

Many R scripts depend on CRAN packages, and most CRAN packages in turn depend on other CRAN packages. If you install an R package, you'll also be installing its dependencies to make it work, and possibly other packages as well to enable its full functionality.

It's been a super-busy time at Strata this week, so I'm taking the easy route for Because it's Friday this week: funny dog and cat videos. If you're not one of the 10 million people who have seen Sad Dog Diary, well, now's your chance:

 

And if you're more of a cat person, there's also Sad Cat Diary:

 

That's all for this week! Have a great weekend, and we'll be back on Monday.

My second-favourite keynote from yesterday's Strata Hadoop World conference was this one, from Pinterest's John Rauser. To many people (especially in the Big Data world), Statistics is a series of complex equations, but a just a little intuition goes a long way to really understanding data.

by Joseph Rickert

There is something about R user group meetings that both encourages, and nourshies a certain kind of "after hours" creativity. Maybe it is the pressure of having to make a presentation about stuff you do at work interesting to a general audience, or maybe it is just the desire to reach a high level of play. But, R user group presentations often manage to make some obscure area of computational statistics seem to be not only accessible, but also relevant and fun. Here are a couple of examples of what I mean.

For the past 7 years, Revolution Analytics has been the leading provider of R-based software and services to companies around the globe. Today, we're excited to announce a new, enhanced R distribution for everyone: Revolution R Open.

Part 2 of a series
by Daniel Hanson, with contributions by Steve Su (author of the GLDEX package)  

Recap of Part 1

In our previous article, we introduced the four-parameter Generalized Lambda Distribution (GLD) and looked at fitting a 20-year set of returns from the Wilshire 5000 Index, comparing the results of two methods, namely the Method of Moments, and the Method of Maximum Likelihood.  

The ability to create reproducible research is an important topic for many users of R. So important, that several groups in the R community have tackled this problem.