An easy way to run R code in parallel on a multicore system is with the mclapply() function. Unfortunately, mclapply() does not work on Windows machines because the mclapply() implementation relies on forking and Windows does not support forking. Previously, I published a hackish solution that implemented a fake mclapply() ... [Read more...]

*** This work has been supported by a grant from the Spencer Foundation (#201400002). The views expressed are those of the author and do not necessarily reflect those of the Spencer Foundation. *** It seems that the heir to WinBUGS is Stan. With Stan, reasonably complex Bayesian models can be expressed in a ... [Read more...]

An easy way to run R code in parallel on a multicore system is with the mclapply() function. Unfortunately, mclapply() does not work on Windows machines because the mclapply() implementation relies on forking and Windows does not support forking. For me, this is somewhat of a headache because I am ... [Read more...]

Last year, Brian Junker, Richard Patz, and I wrote an invited chapter for the (soon to be released) update of the classic text Handbook of Modern Item Response Theory (1996). The chapter is meant to be an update of the … Continue reading → [Read more...]

R speeds up when the Basic Linear Algebra System (BLAS) it uses is well tuned. The reference BLAS that comes with R and Ubuntu isn’t very fast. On my machine, it takes 9 minutes to run a well known R … Continue reading → [Read more...]

On Thursday of last week I gave a short informal talk to Stat Bytes, the CMU Statistics department‘s twice a month computing seminar. Quick tricks for faster R code: Profiling to Parallelism Abstract: I will present a grab bag of … Continue reading → [Read more...]

First, a confession: instead of using classes and defining methods for them, I build a lot of ad hoc data structures out of lists and then build up one-off methods that operate on those lists of lists. I think this … Continue reading → [Read more...]

Disclaimer 1: WinBUGS is old and not maintained. There are other packages to use, if you would like to take advantage of more modern developments in MCMC such as: PyMC which transparently implements adaptive Metropolis-Hastings proposals (among other great features), or the LaplacesDemon R package, which … Continue reading → [Read more...]

I keep trying to write R code like it was C code. It is a habit I’m trying to break myself of. For example, the other day I need to construct a model matrix of 1′s and 0′s in the … Continue reading → [Read more...]

One of the reasons that I don’t often take advantage of the cool features in Revolution R is that I absolutely can’t stand their Visual Studio interface. Previously, if I wanted to run something in RevoR, I fired up the … Continue reading → [Read more...]

This was really frustrating. I’m trying to modify a package from Matt Johnson and although I could get the package he sent me to install flawlessly, I couldn’t un-tar it, make a change, re-tar it, and then R CMD INSTALL … Continue reading → [Read more...]

I wanted a “lightweight” version of Eclipse to run R from Ubuntu. (I installed eclipse-pde using apt-get. It worked fine.) Once it was running, I installed StatEt via the “Install new software” feature from http://download.walware.de/eclipse-3.5. While it was downloading, I … Continue reading → [Read more...]

I take an almost unhealthy pleasure in pushing my computer to its limits. This has become easier with Revolution R and its free license for academic use. One of its best features is debugger that allows you to step through … Continue reading → [Read more...]