Rcpp 0.8.9 was pushed to CRAN recently. Apart from minor bug fixes, this release concentrates on modules, with lots of new features to expose C++ functions and classes through R reference classes. The Rcpp-modules vignette has all the details, a...

The LaTeX typesetting is used to create professional looking documents on a home computer. It may have a steeper learning curve than using a Word Processor, but this initial effort will often pay off reasonably quickly. The system is almost a necessity for anyone writing documents with a large amount of mathematics as most alternatives

A new release 0.8.9 of Rcpp is now available at CRAN and has just been uploaded to Debian. As always, sources are also available from my local directory here. This release comes a few weeks after the preceding 0.8.8 release and continues with a ...

I’ve just received my copy of Advanced Markov Chain Monte Carlo Methods, by Liang, Liu, & Carroll. Although my PhD didn’t really involve any Bayesian methodology (and my undergrad was devoid of any Bayesian influence), I’ve found that the sort of problems I’m now tackling in systems biology demand a Bayesian/MCMC approach. There are a

Conrad Sanderson released version 1.0.0 of Armadillo, his templated C++ library for linear algebra, earlier this week. So congratulations to Conrad on reaching 1.0.0! I folded his version 1.0.0 into a new release 0.2.10 of RcppArmadillo, our Rcpp-base...

Many from the R world will know The R Inferno. Abstract: If you are using R and you think you’re in hell, this is a map for you. A newly minted inferno is The 9 circles of scientific hell. Most amusing to me is Circle 4: p-value fishing, the punishment of which is brilliant. As … Continue reading...

The increasing number of R-oriented Bayesian computational tools such as MCMCpack, MCMCglmm, DPpackage, R-INLA, spBayes, have made BUGS less and less crucial for day to day Bayesian computation. Honestly, I cannot figure out a single analysis that BUGS...

The increasing number of R-oriented Bayesian computational tools such as MCMCpack, MCMCglmm, DPpackage, R-INLA, spBayes, have made BUGS less and less crucial for day to day Bayesian computation. Honestly, I cannot figure out a single analysis that BUGS...

In this post I present an example of using Sweave to prepare a PDF of formatted multiple choice questions. More broadly the example shows how to use Sweave to incorporate elements of a database into a formatted LaTeX document. It aims to be useful to anyone wanting to learn more about the almost magical powers of make, Sweave,...

It's holiday time here in the US, so we're taking a break at Revolutions. We'll be back with more R goodness on Monday, but in the meantime, think of the turkeys. R-chart: Don't be a Turkey

Feature selection is the data mining process of selecting the variables from our data set that may have an impact on the outcome we are considering. For commercial data mining, which is often characterised by having too many variables for model building, this is an important step in the analysis process. And since we often work on...

Kaggle, the predictive-analytics competition site, has analyzed the preferences of the 2,500 data scientists who participate in its competitions, and R was the most-preferred software of the competitors at 22.5%. The next-nearest alternative was Matlab, at 16%. On a related note, the premier of the Australian state of New South Wales has just launched a competition on Kaggle to...

Kaggle, the predictive-analytics competition site, has analyzed the preferences of the 2,500 data scientists who participate in its competitions, and R was the most-preferred software of the competitors at 22.5%. The next-nearest alternative was Matlab, at 16%. On a related note, the premier of the Australian state of New South Wales has just launched a competition on Kaggle to...

Principal component analysis (PCA) is a mathematical transformation of possibly(correlated) variables into a number of uncorrelated variables called principal components. The resulting components from this transformation is defined in such a way that t...

Principal component analysis (PCA) is a mathematical transformation of possibly(correlated) variables into a number of uncorrelated variables called principal components. The resulting components from this transformation is defined in such a way that t...

Here are the slides from the first University of Utah and Research Park R Users Group meeting. They discuss getting help and finding packages. R

Nathan Yau has just published at FlowingData a step-by-step guide on making bubble charts in R. It's actually pretty simple: read in data, sqrt-transform the "bubble" variable (to scale the bubbles by area, not radius), and use the symbols function to plot. It's the last step, though, that really ups the presentation quality: read R's PDF file into Illustrator...

R and the NYC R User Group get brief mentions in this article about AOL's offices in New York City. The NYC UseRs meet at AOL and (ironically) the next meeting on Dec 9 is on the topic of R at Google. New York Observer: Bringing Some Sizzle to the Dial-Up King (via)

Each year I have the pleasure (actually it’s quite fun) of teaching R programming to first year mathematics and statistics students. The vast majority of these students have no experience of programming, yet think they are good with computers because they use facebook! The class has around 100 students, and there are eight practicals. In