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StatEt in Ubuntu 10.04

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...

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Messing with R packages

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...

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Revolution R with Eclipse Helios

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...

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R is not C

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 standard, counting in...

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Getting R2WinBUGS to talk to WinBUGS 1.4 on Ubuntu 12.04 LTS

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...

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Managing memory in a list of lists data structure

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....

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My Stat Bytes talk, with slides and code

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:...

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For faster R use OpenBLAS instead: better than ATLAS, trivial to switch to on...

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...

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Writing a Metropolis-Hastings within Gibbs sampler in R for a 2PL IRT model...

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 itself is...

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Implementing mclapply() on Windows: a primer on embarrassingly parallel...

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...

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