Most statistical models used in experimental psychology are designed to estimate the mean of a response variable given some set of predictors. This is all well and good when errors are largely symmetric and our predictors are expected to primarily … Read more
It’s difficult to analyze trajectory data, since the “object” of analysis (the trajectory) can’t easily be summarized by a single value without throwing away large amounts of information, unless you already know what you’re looking for (e.g. if you’re looking … Read more
I’m swimming in reaction time data at the moment. My usual approach to analyzing reaction times in cognitive psychology is through some sort of normal random effects model of the log or inverse RT. This is really only good for … Read more
Echo-state networks (ESN’s) are a class of neural network designed to work with temporal data. I normally don’t like neural networks, since they rarely actually tell you anything interpretable about your data (and they pretty much just do regression anyway), … Read more
I’ve been experimenting with techniques for robust regression, and I thought that it would be a fun excercise to implement a robust variant of the simple linear regression model based on the t-distribution.
The term “outlier” is used very … Read more