In case you missed them, here are some articles from August of particular interest to R users.
A contest to showcase applications of R for businesses is offering $20,000 in prizes from Revolution Analytics.
Three new open-source packages integrating R and Hadoop will be introduced by Revolution Analytics' CTO David Champagne in a webinar on September 21.
Dirk Eddelbuettel will present live one-day master classes on programming with Rcpp in New York (Sep 24) and San Francisco (Oct 8).
R Core member Luke Tierney announced at JSM that R 2.14 will be faster, with the byte compiler used for base and recommended packages.
Three Google employees talk about how they use R at JSM.
Survey respondents at JSM consider themselves data scientists, expect usage of R and Revolution R to grow.
An open-source analyst profiles Revolution Analytics and remarks on big-data applications of R.
An R user at ANZ bank in Australia talks about how he uses R for credit risk analysis.
Two grad students at University of Michigan use R to determine what factors most influence the selection committee for the Hockey Hall of Fame.
FastCompany published an article on “telling stories with data”, featuring two websites that often use R, FlowingData and the OkTrends blog.
News from the Revolution Analytics August newsletter.
You can install Emacs with the ESS interface to R on Windows and Macs in less than 2 minutes.
I gave a talk at useR! on the R Ecosystem: the R project, the R community, and companies using and working with R.
R Core member Brian Ripley gave some insights into R's development process, and the future of R, in his talk at useR!.
A profile of Martyn Plummer, R core member and contributor to several R packages for epidemiology and Bayesian analysis.
Joseph Rickert uses the RevoScaleR package to look at the residuals from a large linear model.
In a tongue-in-cheek post, Business Intelligence analyst Steve Miller “complains” that there's too much new stuff in R.
The slides and replay from the recent Revolution Analytics webinar, 100% R and More, are available for download.
Jeroen Ooms' new project, OpenCPU, lets you embed live R graphics in web pages.
An analysis of the R source tree reveals that about 50% of R is written in C, while R packages on CRAN are about 50% R.
A new white paper by Norman Nie looks at the impact of statistical analysis methodology on working with Big Data.
As always, thanks for the comments and please send any suggestions to me at [email protected]. Don't forget you can follow the blog using an RSS reader like Google Reader, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.