Blog Archives

parallelsugar: An implementation of mclapply for Windows

October 14, 2015
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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() for Windows users with one

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rstanmulticore: A cross-platform R package to automatically run RStan MCMC chains in parallel

May 1, 2015
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*** 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 compact way

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Implementing mclapply() on Windows: a primer on embarrassingly parallel computation on multicore systems with R

July 14, 2014
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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 used to using mclapply(), and

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Writing a Metropolis-Hastings within Gibbs sampler in R for a 2PL IRT model (9 posts)

November 5, 2013
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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 →

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

July 9, 2013
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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 →

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My Stat Bytes talk, with slides and code

June 24, 2013
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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 →

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Managing memory in a list of lists data structure

April 3, 2013
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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 →

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Getting R2WinBUGS to talk to WinBUGS 1.4 on Ubuntu 12.04 LTS

May 4, 2012
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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 →

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R is not C

December 7, 2011
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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 →

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Revolution R with Eclipse Helios

January 10, 2011
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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 →

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