Publications by Simon Barthelme
Predicting spatial locations using point processes
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 sort of thing. Related To leave a comment for the author, please follow the li...
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Fitting psychometric functions using STAN
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 using STAN and R, in case that’s useful to psychophysicists out there. ...
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ECVP tutorial on classification images
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 the slides in R Markdown, use knit...
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cMDS: visualising changing distances
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 metric you can use, but often what you have is a family of possible d...
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New package for image processing in R
I’ve written a package for image processing in R, with the goal of providing a fast API in R that lets you do things in C++ if you need to. The package is called imager, and it’ on Github. The whole thing is based on CImg, a very nice C++ library for image processing by David Tschumperlé. Features: Handles images in up to 4 dimensions, mea...
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imager now on CRAN, and a non-linear filtering example
imager is an R package for image processing that’s fairly fast and now quite powerful (if I may say so myself). It wraps a neat C++ library called CImg, by David Tschumperlé (CNRS). It took quite a bit of work, but imager is now on CRAN, so that installing it is as easy as: install.packages("imager") Here’s an example of using imager for ma...
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New R package for Eyelink eye-trackers
Eyelink eye-trackers output an avalanche of disorganised crap. I’ve written an R package that will hopefully filter that crap for you. It’s called eyelinker and it’s on Github. It outputs a set of dataframes containing raw traces, saccades, fixations and blinks, meaning it’s easy to produce plots like this one: There’s a vignette expla...
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New features in imager 0.20
imager, an R package for image processing, has been updated to v0.20 on CRAN. It’s a major upgrade with a lot of new features, better documentation and a more consistent API. imager now has 130 functions, and I myself keep forgetting all that’s in there. I’ve added a tutorial vignette that should help you get started. It goes through a few ...
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New features in imager 0.30
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) Experimental support f...
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vecpack: an R package for packing stuff into vectors
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 is to write a likelihood function that takes as many arguments as you have parameters in your mo...
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