The R core group has quickly followed up with a patch to R version 3. Announced yesterday, R 3.0.1 (code name: "Good Sport") improves serialization performance with big objects, improves reliability for parallel programming and fixes a few minor bugs. (You can find the complete list of changes in the NEWS file.) The source distribution and Windows and Linux...
Blog Archives
Revolution Newsletter: May 2013
The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full May edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Gaming Analytics FTW! Join us on 13Jun13 at 10:00 AM PDT for our webinar...
Statistics vs Data Science vs BI
As someone who trained as a statistician, I've always struggled with that title. I love the rigor and insight that Statistics brings to data analysis, but let's face it: Statistics — the name — has always had a bit of a branding problem. Telling someone I was a statistician was more likely to conjure up images of me counting...
Top 3 R resources for beginners
The community team at Revolution Analytics has just updated this list of resources to learn about R on the Web. Included is this list of the top 3 resources for absolute beginners getting started with R: An Introduction to R – The free, “official” CRAN R Manual Try R – a short course that lets you jump right in...
In case you missed it: April 2013 Roundup
In case you missed them, here are some articles from April of particular interest to R users: A critique of a SAS whitepaper comparing the performance of SAS, R and Mahout. A video presentation from statistician Tess Nesbitt at UpStream, who uses GAM survival models in R for marketing attribution analysis. The April edition of the Revolution Analytics newsletter....
A guide to speeding up R code
Noam Ross recently shared a very useful guide to speeding up your R code. Get a bigger computer (for example, renting an instance on the Amazon cloud for a few cents an hour) Use parallel programming techniques Using the R byte-compiler Profiling and benchmarking your code Using high-performance packages (like xts, for time series) And lastly, rewriting your code...
What’s new in Revolution R Enterprise 6.2 (video)
If you missed last week's webinar, product manager Thomas Dinsmore shared details of the new features in Revolution R Enterprise 6.2 in the video below: You can also download slides of the presentation at the link below. Revolution Analytics webinars: What's New in Revolution R Enterprise 6.2
Explaining real-time predictive analytics with big data (video)
In my presentation to the Strata Santa Clara 2013 conference earlier this year, my goal was to give a succinct (under 20 minutes!) explanation of three terms that are two often used as mere buzzwords: predictive analytics, real time, and big data. You can download the slides for my presentation, Real-time Big Data Analytics: From Deployment to Production, from...
NYT uses R to investigate NFL draft picks
Last week, the New York Times published online an interactive tool to explore NFL draft picks, revealing the fact that there's not much relationship between an early pick and the star performers in the season: Kevin Quealy, graphics editor at the NYT, detailed the process behind creating this graphic on his chartsnthings blog. He and others on the graphics...
How UpStream uses R for Attribution Analysis
Major retailers like Williams Sonoma use UpStream Software for marketing analytics, including revenue attribution, targeting, and optimization. In the video below Tess Nesbitt (senior statistician at UpStream) describes how she uses Revolution R Enterprise and Hadoop to figure out the impact on various marketing channels (for example direct mail, email offers, and catalogs) on consumer retail sales. (The slides...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
