“In place of past experience, frequentism considers future behavior: an optimal estimator is one that performs best in hypothetical repetitions of the current experiment. The resulting gain in scientific objectivity has carried the day…” Julien Cornebise sent me this Science column by Brad Efron about Bayes’ theorem. I am a tad surprised that it got […]

## Search Results

## Bayes’ Theorem in the 21st Century, really?!

June 20, 2013## abstract for “Bayes’ Theorem: then and now”

March 19, 2013Here is my abstract for the invited talk I will give at EMS 2013 in Budapest this summer (the first two banners were sites of EMS 2013 conferences as well, which came above the European Meeting of Statisticians on a Google search for EMS 2013): What is now called Bayes’ Theorem was published and maybe […]

## Bayes’ Theorem

January 22, 2009There is a very long and somehow windy—if often funny—introduction to Bayes’ theorem by a researcher in artificial intelligence. In particular, it contains several Java applets that shows how intuition about posterior probabilities can be wrong. The whole text is about constructing Bayes’ theorem for simple binomial outcomes with two possible causes. It is indeed […]

## O’Bayes 19/3.5

July 3, 2019Among the posters at the second poster session yesterday night, one by Judith ter Schure visually standing out by following the #betterposter design suggested by Mike Morrison a few months ago. Design on which I have ambivalent feelings. On the one hand, reducing the material on a poster is generally a good idea as […]

## O’Bayes 19/2

July 1, 2019One talk on Day 2 of O’Bayes 2019 was by Ryan Martin on data dependent priors (or “priors”). Which I have already discussed in this blog. Including the notion of a Gibbs posterior about quantities that “are not always defined through a model” [which is debatable if one sees it like part of a semi-parametric […]