I was thinking about new material that I will use for teaching this coming semester (starting the third week of February) and suddenly compiled the following list of links: William Briggs writes It is time to stop teaching Frequentism to … Continue reading →
Around Christmas time I presented my first impressions of Kruschke’s Doing Bayesian Data Analysis. This is a very nice book but one of its drawbacks was that part of the code used BUGS, which left mac users like me stuck. … Continue reading →
About a month ago I was discussing the approach that I would like to see in introductory Bayesian statistics books. In that post I mentioned a PDF copy of Doing Bayesian Data Analysis by John K. Kruschke and that I … Continue reading →
This paper by Brad Efron came to my knowledge when I was looking for references on Bayesian bootstrap to answer a Cross Validated question. After reading it more thoroughly, “Bayesian inference and the parametric bootstrap” puzzles me, which most certainly means I have missed the main point. Indeed, the paper relies on parametric bootstrap—a...
After attending two one-day workshops last week I spent most days paying attention to (well, at least listening to) presentations in this biostatistics conference. Most presenters were R users—although Genstat, Matlab and SAS fans were also present and not one … Continue reading →
This post is somewhat marginal to R in that there are several statistical systems that could be used to tackle the problem. Bayesian statistics is one of those topics that I would like to understand better, much better, in fact. … Continue reading →
The below is taken from a work in progress: The Polya urn is a heuristic associated with Dirichlet process mixtures. We present the scheme in a modified format, using balloons instead of balls, where the probability of drawing a balloon from the urn is proportional to its volume. Balloons are preferred because their volume...
I don't know, of course, because the evidence at hand is based on my experience. But, I'll leave the reader to consider whether these observations generalize. Proponents of Bayesian statistical inference argue that Bayesian credible intervals are more intuitive than the frequentist confidence intervals, because the Bayesian inference is a probability statement about a...
A few years ago we had this really cool idea: we had to establish a trial to understand wood quality in context. Sort of following the saying “we don’t know who discovered water, but we are sure that it wasn’t … Continue reading →
This week I’m facing my—and many other lecturers’—least favorite part of teaching: grading exams. In a supreme act of procrastination I will continue the previous post, and the antepenultimate one, showing the code for a bivariate analysis of a randomized … Continue reading →
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).