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Here’s a problem I’ve had again and again: let’s say you’ve defined a statistical model with several parameters. One of them is a scalar. Another is a matrix. The third one is a vector, and so on. When fitting the model the natural thing to do ... [Read more...]

imager is an R package for image processing, based on CImg. This new release brings many new features, including: Support for automatic parallel processing using OpenMP. A new S3 class, imlist, which makes it easy to work with image lists New functions for interactively selecting image regions (grabRect,grabPoint,grabLine) ... [Read more...]

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Gina Gruenhage has just arxived a new paper describing an algorithm we call cMDS. Here’s what it’s for: if you do any kind of data analysis you often find yourself comparing datapoints using some kind of distance metric. All’s well if you have a unique reasonable distance ... [Read more...]

The slides for my ECVP tutorial on classification images are available here. Try this alternative version if the equations look funny. (image from Mineault et al. 2009) The slides are in HTML and contain some interactive elements. They’re the result of experimenting with R Markdown, D3 and pandoc. You write ... [Read more...]

STAN is a new system for Bayesian inference, similar to BUGS and JAGS. I’ve played with it a bit and it’s quite promising, it really has the potential to make MCMC less of a pain (on simple models). I’ve written a short introduction to fitting psychometric functions ... [Read more...]

I’ve uploaded a draft tutorial on some aspects of prediction using point processes. I wrote it using R-Markdown, so there’s bits of R code for readers to play with. It’s hosted on Rpubs, which turns out to be a great deal more convenient than WordPress for that ... [Read more...]

Regular expressions are a fantastic tool when you’re looking for patterns in time series. I wish I’d realised that sooner. Here’s a timely example: traditionally, when you have two successive quarters of negative GDP growth, you’re in recession. We have a quarterly GDP time series for ... [Read more...]

Barycentric interpolation generalises linear interpolation to arbitrary dimensions. It is very fast although suboptimal if the function is smooth. You might now it as algorithm 21.7.1 in Numerical Recipes (Two-dimensional Interpolation on an Irregular Grid). Using package geometry it can be implemented in a few lines of code in R. Here’... [Read more...]

Have you ever seen these scatterplots that report a significant correlation between X and Y, and look like it’s just the one point to the upper-right driving the correlation? Thanks to this interactive tool, you too can do this at home. [Read more...]

Here’s a sneak peak into upcoming visualisation work. I’ve been working a bit on MDS (Multi-dimensional scaling), a classical technique for visualising distance data. Classical MDS is useful, but interactive MDS is *much* more useful. Using D3, a Javascript visualisation framework, it’s relatively easy to make interactive ... [Read more...]

[of interest mostly to French and R bilinguals] La prochaine édition des Rencontres R aura lieu à Lyon en Juillet prochain. Ci-dessous, l’appel officiel à contributions. ————————————————– Appel à communication des 2èmes Rencontres R : Dans la lignée de la conférence internationale Use’R et suite à la première édition qui a ... [Read more...]

Here’s a code snippet I thought I’d share. Very often I find myself checking the output of a function f(a,b) for a lot of different values of a and b, which I then need to plot somehow. An example: here’s a function that computes the ... [Read more...]

Ken Knoblauch wrote to inform me that Springer has just released a book he coauthored with Larry Maloney on statistical methods in psychophysics. The book is called “Modeling Psychophysical Data in R” and covers both classical psychophysical analyses (Signal Detection Theory) and more recent methods (e.g. Mixed Models). Ken ... [Read more...]