A while back I wrote about how the classical non-parametric bootstrap can be seen as a special case of the Bayesian bootstrap. Well, one difference between the two methods is that, while it is straightforward to roll a classical bootstrap in R, there is no easy way to do a ... [Read more...]

hygge A Danish word (pronounced HU-guh) meaning social coziness. I.e. the feeling of a good social atmosphere. – Urban Dictionary Yes, there was plenty of hygge to go around this year’s UseR! that took place last week in Aalborg, Denmark. Everybody I’ve spoken with agrees that it was ... [Read more...]

In a previous post I used the the Million Base 2.2 chess data base to calculate the predictive piece values of chess pieces. It worked out pretty well and here, just for fun, I thought I would check out what happens with the predictive piece values over the course of a ... [Read more...]

Who doesn’t like chess? Me! Sure, I like the idea of chess – intellectual masterminds battling each other using nothing but pure thought – the problem is that I tend to loose, probably because I don’t really know how to play well, and because I never practice. I do know ... [Read more...]

The non-parametric bootstrap was my first love. I was lost in a muddy swamp of zs, ts and ps when I first saw her. Conceptually beautiful, simple to implement, easy to understand (I thought back then, at least). And when she whispered in my ear, “I make no assumptions regarding ... [Read more...]

Everybody loves speed comparisons! Is R faster than Python? Is dplyr faster than data.table? Is STAN faster than JAGS? It has been said that speed comparisons are utterly meaningless, and in general I agree, especially when you are comparing apples and oranges which is what I’m going to ... [Read more...]

“Behind every great point estimate stands a minimized loss function.” – Me, just now This is a continuation of Probable Points and Credible Intervals, a series of posts on Bayesian point and interval estimates. In Part 1 we looked at these estimates as graphical summaries, useful when it’s difficult to plot ... [Read more...]

Peter Norvig, the director of research at Google, wrote a nice essay on How to Write a Spelling Corrector a couple of years ago. That essay explains and implements a simple but effective spelling correction function in just 21 lines of Python. Highly recommended reading! I was wondering how many lines ... [Read more...]

Christmas is soon upon us and here are some gift ideas for your statistically inclined friends (or perhaps for you to put on your own wish list). If you have other suggestions please leave a comment! :) 1. Games of probability A recently released game where probability takes the main role is ... [Read more...]

Making a slight digression from last month’s Probable Points and Credible Intervals here is how to summarize a 2D posterior density using a highest density ellipse. This is a straight forward extension of the highest density interval to the situation where you have a two-dimensional posterior (say, represented as ... [Read more...]

Why R? Because S! R is the open source implementation (and a pun!) of S, a language for statistical computing that was developed at Bell Labs in the late 1970s. After that, the implementation of S underwent a number of major revisions documented in a series of seminal books, often ... [Read more...]

After having broken the Bayesian eggs and prepared your model in your statistical kitchen the main dish is the posterior. The posterior is the posterior is the posterior, given the model and the data it contains all the information you need and anything else will be a little bit less ... [Read more...]

Big data is all the rage, but sometimes you don’t have big data. Sometimes you don’t even have average size data. Sometimes you only have eleven unique socks: Karl Broman is here putting forward a very interesting problem. Interesting, not only because it involves socks, but because it ... [Read more...]

As the normal distribution is sort of the default choice when modeling continuous data (but not necessarily the best choice), the Poisson distribution is the default when modeling counts of events. Indeed, when all you know is the number of events during a certain period it is hard to think ... [Read more...]

Inspired by events that took place at UseR 2014 last month I decided to implement an app that estimates one’s blood alcohol concentration (BAC). Today I present to you drinkR, implemented using R and Shiny, Rstudio’s framework for building web apps using R. So, say that I had a ... [Read more...]

This year’s UseR! conference was held at the University of California in Los Angeles. Despite the great weather and a nearby beach, most of the conference was spent in front of projector screens in 18° c (64° f) rooms because there were so many interesting presentations and tutorials going on. I ... [Read more...]

Even though I said it would never happen, my silly package with the sole purpose of playing notification sounds is now on CRAN. Big thanks to the CRAN maintainers for their patience! For instant gratification run the following in R to install beepr and make R produce a notification sound: {{... [Read more...]

Does pill A or pill B save the most lives? Which web design results in the most clicks? Which in vitro fertilization technique results in the largest number of happy babies? A lot of questions out there involves estimating the proportion or relative frequency of success of two or more ... [Read more...]

As I’m more or less an autodidact when it comes to statistics, I have a weak spot for books that try to introduce statistics in an accessible and pedagogical way. I have therefore collected what I believe are all books that introduces statistics using comics (at least those written ... [Read more...]

While reading up on quantile regression I found a really nice hack described in Bayesian Quantile Regression Methods (Lancaster & Jae Jun, 2010). It is called Jeffreys’ substitution posterior for the median, first described by Harold Jeffreys in his Theory of Probability, and is a non-parametric method for approximating the posterior of ... [Read more...]