Much has been said about how the game of Quidditch is ruined by the scoring system – specifically how it makes no sense that the snitch is worth 150 points and that catching it ends the game [1, 2, 3]. Most of these arguments seem to revolve around the claim that it is nearly impossible to win a match of Quidditch without catching the snitch. Is this true? Let’s try and answer this question formally using statistics and R simulations:

We already saw the power of the OneR package in the preceding post. Here we want to give some more examples to gain some fascinating, often counter-intuitive, insights.

Another minor release 0.3.3.5.0 of RcppEigen arrived on CRAN today (and just went to Debian too) bringing support for Eigen 3.3.5 to R.

In this post in the R:case4base series we will look at string manipulation with base R, and provide an overview of a wide range of functions for our string working needs.

Case Study Example 1: An eCommerce Company Evaluation

RStudio 1.2 Preview: The Little Things

I have completed the polishing/correcting/fiddling of the eight statistical analysis related chapters of my evidence-based software engineering book, and an updated draft pdf is now available (download here).

Since publishing the monotonic binning function based upon the isotonic regression (https://statcompute.wordpress.com/2017/06/15/finer-monotonic-binning-based-on-isotonic-regression), I’ve received some feedback from peers. A potential concern is that, albeit improving the granularity and predictability, the binning is too fine and might not generalize well in the new data.

Just for fun, I decided to compare the estimates from lmer and INLA for the variance components of an LMM (this isn’t really something that you would ordinarily do – comparing frequentist and bayesian approaches). The codes are below. A couple of plots are drawn, which show the distribution of the hyperparameters (in this case variances) from INLA, which are difficult to get from the frequentist framework (there’s a link to a presentation by Douglas Bates in the code, detailing why you might not want to do it [distribution is not symmetrical], and how you could do it… but it’s a lot of work).

Simulating Spreading Activation in a Network (spreadr)The notion of spreading activation is a prevalent metaphor in the cognitive sciences. This package provides the tools for cognitive scientists and psyc …