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• If you are writing a book on Bayesian statistics

  This post is somewhat marginal to R in that there are several statistical systems that could be used to tackle…
  24 Nov, '11

• No one would ever conceive

  皿 I believe that no one who is familiar, either with mathematical advances in other fields, or with the range of…
  23 Nov, '11

• Do we need to deal with ‘big data’ in R?

  David Smith at the Revolutions blog posted a nice presentation on “big data” (oh, how I dislike that term). It…
  22 Nov, '11

• Surviving a binomial mixed model

  A few years ago we had this really cool idea: we had to establish a trial to understand wood quality…
  12 Nov, '11

• On “true” models

  皿 Before starting the description of the probability distributions, we want to impose on the reader the essential feature that a…
  8 Nov, '11

• Coming out of the (Bayesian) closet: multivariate version

  This week I’m facing my—and many other lecturers’—least favorite part of teaching: grading exams. In a supreme act of procrastination…
  8 Nov, '11

• Coming out of the (Bayesian) closet

  Until today all the posts in this blog have used a frequentist view of the world. I have a confession…
  4 Nov, '11

• Teaching with R: the tools

  I bought an Android phone, nothing fancy just my first foray in the smartphone world, which is a big change…
  2 Nov, '11

• Multivariate linear mixed models: livin’ la vida loca

  I swear there was a point in writing an introduction to covariance structures: now we can start joining all sort…
  1 Nov, '11

• Covariance structures

  In most mixed linear model packages (e.g. asreml, lme4, nlme, etc) one needs to specify only the model equation (the…
  27 Oct, '11