In case you missed them, here are some articles from May of particular interest to R users:
Karl Broman's hipsteR guide lists some new(ish) features of R that early adopters may have missed.
Joseph Rickert reviews the R/Finance 2014 conference and summarizes the R packages presented there. Plus, a review of R's impact on computational finance, with links to many resources.
A recent Revolution Analytics webinar compares the speed of Revolution R Enterprise and SAS for statistical calculations on large data sets.
A tutorial on the “plotly” R package to generate online plotly graphics from R graphics commands. If you're new to plotly, here's an introduction.
David Smith's keynote presentation at the China R Users Conference describes how many companies and organizations use R to analyze data.
A Microsoft paper describes the Bayesian model behind multiplayer matchmaking in online Xbox games.
Continuing his series of posts about ensemble models, Mike Bowles looks at big-data random forests with Revolution R Enterprise.
R will be used to design the T-shirt for the useR! 2014 conference.
Data scientists at Facebook present an online course on exploratory data analysis with R.
A scientist uses self-experimentation and R to find the worst place to be stung by a bee.
Scott Chamberlain's “R for Cats” is a fun introduction to the R language.
A feature article in FastCoLabs looks at how R is used at companies.
Using Rcpp to speed up code investigating the Collatz Conjecture.
Revolution Analytics introduces AdviseR, a service offering technical support to all R users.
A tutorial on importing semistructured data with the rxImport function of Revolution R Enterprise.
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, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.