At a talk I saw at the useR!2012 conference last month, Googler Karl Millar estimated that there are at least 200 active R users at Google, plus another 300+ occasional users participating in Google's internal R support list. But what are all these Google employees doing with R? A post from the ... [Read more...]

News is starting to leak that the Large Hadron Collider may have accomplished its primary mission of confirming the existence of the hypothesised and heretofore elusive subatomic particle, the Higgs Boson. And sure, billions of Euros worth of state-of-the-art high-energy machinery and an army of experimental and theoretical physicists probably ... [Read more...]

R is an incredibly comprehensive statistics package. Even if you just look at the standard R distribution (the base and recommended packages), R can do pretty much everything you need for data manipulation, visualization, and statistical analysis. And for everything else, there's more than 5000 packages on CRAN and other repositories, ... [Read more...]

R''s glm function for generalized linear modeling is very powerful and flexible: it supports all of the standard model types (binomial/logistic, Gamma, Poisson, etc.) and in fact you can fit any distribution in the exponential family (with the family argument). But if you want to use it on a ... [Read more...]

CIO.com recently published its list of 9 open-source technologies to watch. Hadoop is first on the list, and second up is the R Project: R is an open source programming language and software environment designed for statistical computing and visualization. R was designed by Ross Ihaka and Robert Gentleman at ... [Read more...]

Last week, Joe Rickert used R and four years of US Census data to create an image plot of the relative probabilities of being born on a given day of the year: Chris Mulligan also tackled this problem with R, but this time using 20 years of Census data from 1969 to 1988. ... [Read more...]

We're definitely in the age of Big Data: today, there are many more sources of data readily available to us to analyze than there were even a couple of years ago. But what about extracting useful information from novel data streams that are often noisy and minutely transactional ... aye, there's ... [Read more...]

Earlier this week, Revolution Analytics' Joe Rickert gave a webinar Introduction to R for Data Mining. You can watch the replay below: If you're already familiar with R and the basics of data mining, you might want to skip ahead to the 13-minute mark where Joe's live demo begins. There ... [Read more...]

You've probably heard of the Birthday Paradox: it only takes a small gathering of people before it's quite likely that two of them share the same birthday. You can solve the problem analytically or with simulation, but usually in either case simplifying assumptions are made (no-one born on February 29, for ... [Read more...]

Revolution Analytics is proud to announce the latest update to our enhanced, production-grade distribution of R, Revolution R Enterprise. This update expands the range of supported computation platforms, adds new Big Data predictive models, and updates to the latest stable release of open source R (2.14.2), which improves performance of the ... [Read more...]

Following the announcement of the US Government Big Data Initiative, I was asked to write a small article about applications of R in government. The article has just appeared in Government Security News (and I believe will appear in their daily newsletter tomorrow). In the article, I highlighted several R ... [Read more...]

In computing, social networks are traditionally represented as graphs: a connection of nodes (people), pairs of which may be connected by edges (friend relationships). Visually, the social networks can then be represented like this: Social network analysis often amounts to calculating the statistics on a graph like this: the number ... [Read more...]

An interview with Revolution Analytics CEO Dave Rich was published this week by BeyeNetwork. During the interview, Dace was asked about how the statistical modeling platforms have changed over the decades: People have been doing statistical modeling and predictive analytics for 50 years now, SAS and SPSS have been around since ... [Read more...]

Sameer Chopra, vice president of Advanced Analytics at Orbitz Worldwide, wrote recently in Analytics magazine about the changing landscape of processes, software and systems for statistical modelers. In a section on "Big Data and Open Source Analytics", Chopra lays out the reasons why the R language "has become the data-mining ... [Read more...]

We had a great Twitter conversation last Thursday on the use of big-data analytics, Revolution R Enterprise, and IBM Netezza in the search for a cure for MS. Many thanks to the other panelists: Murali Ramanathan (SUNY Buffalo), Tim Coetzee (National MS Society) and moderator Shawn Dolley (IBM) for fielding ... [Read more...]

The story about the great work that SUNY Buffalo has been doing to find a cure for Multiple Sclerosis with Revolution R Enterprise and IBM Netezza has generated a lot of attention, with stories in Forbes, InformationWeek and eWeek (amongst others). To continue the discussion, IBM has put together a ... [Read more...]

by Yanchang Zhao, RDataMining.com Compared with many other programming languages, such as C/C++ and Java, R is less efficient and consumes much more memory. Fortunately, there are some packages that enables parallel computing in R and also packages for processing … Continue reading → [Read more...]

The open-source RHadoop project makes it easier to extract data from Hadoop for analysis with R, and to run R within the nodes of the Hadoop cluster -- essentially, to transform Hadoop into a massively-parallel statistical computing cluster based on R. In yesterday's webinar (the replay of which is embedded ... [Read more...]

Douglas Merrill, former CIO/VP of Engineering at Google, writes in Forbes about using the R language for data analysis: Most folks with math-oriented graduate degrees will have written something in R, a non-commercial option for your big data analysis. So, great graduates from great graduate schools know great tools. ... [Read more...]

Github has made data on its code repositories, developer updates, forks etc. from the public GitHub timeline available for analysis, and is offering prizes for the most interesting visualization of the data. Sounds like a great challenge for R programmers! The R language is currently the 26th most popular on ... [Read more...]