Coding algorithms in R for models written in Stan

Hi all, On top of recommending the excellent autobiography of Stanislaw Ulam, this post is about using the software Stan, but not directly to perform inference, instead to obtain R functions to evaluate a target’s probability density function and its gradient. With which, one can implement custom methods, while still benefiting from the great workContinue reading “Coding algorithms in R for models written in Stan”

Moustache target distribution and Wes Anderson

Today I am going to introduce the moustache target distribution (moustarget distribution for brievety). Load some packages first. Let’s invoke the moustarget distribution. This defines a target distribution represented by a SVG file using RShapeTarget. The target probability density function is defined on and is proportional to on the segments described in the SVG files,Continue reading “Moustache target distribution and Wes Anderson”

Using R in LaTeX with knitr and RStudio

Hi, I presented today at INSEE R user group (FLR) how to use knitr (Sweave evolution) for writing documents which are self contained with respect to the source code: your data changed? No big deal, just compile your .Rnw file again and you are done with an updated version of your paper![Ctrl+Shift+I] is easy. SomeContinue reading “Using R in LaTeX with knitr and RStudio”

GPUs in Computational Statistics

Hey, Next week the Centre for Research in Statistical Methodology (CRiSM, in Warwick, UK) will be hosting a workshop on the use of graphics processing units in statistics, a quickly expanding area that I’ve blogged about here. Xian and I are going to talk about Parallel IMH and Parallel Wang Landau. We’ll be able toContinue reading “GPUs in Computational Statistics”

Google Fusion Tables

A quick post about another Google service that I discovered recently called Fusion Tables. There you can store, share and visualize data up to 250 MB, of course in the cloud. With Google Docs, Google Trends and Google Public Data Explore, it is another example of Google’s efforts to gain ground in data management. HasContinue reading “Google Fusion Tables”

PAWL package on CRAN

The PAWL package (which I talked about there, and which implements the parallel adaptive Wang-Landau algorithm and adaptive Metropolis-Hastings for comparison) is now on CRAN! which means that within R you can easily install it by typing install.packages(“PAWL”) Isn’t that amazing? It’s just amazing. Kudos to the CRAN team for their quickness and theirContinue reading “PAWL package on CRAN”