Archive for Holland

Amsterdamse huizen

Posted in pictures, Running, Travel, University life with tags , , , on April 19, 2015 by xi'an


Amsterdam XXX [very hot]

Posted in pictures, Running, Travel with tags , , , , , , on April 17, 2015 by xi'an


reis naar Amsterdam

Posted in Books, Kids, pictures, Running, Statistics, Travel, University life, Wines with tags , , , , , , , , , , , , , on April 16, 2015 by xi'an

Amster4On Monday, I went to Amsterdam to give a seminar at the University of Amsterdam, in the department of psychology. And to visit Eric-Jan Wagenmakers and his group there. And I had a fantastic time! I talked about our mixture proposal for Bayesian testing and model choice without getting hostile or adverse reactions from the audience, quite the opposite as we later discussed this new notion for several hours in the café across the street. I also had the opportunity to meet with Peter Grünwald [who authored a book on the minimum description length principle] pointed out a minor inconsistency of the common parameter approach, namely that the Jeffreys prior on the first model did not have to coincide with the Jeffreys prior on the second model. (The Jeffreys prior for the mixture being unavailable.) He also wondered about a more conservative property of the approach, compared with the Bayes factor, in the sense that the non-null parameter could get closer to the null-parameter while still being identifiable.

Amster6Among the many persons I met in the department, Maarten Marsman talked to me about his thesis research, Plausible values in statistical inference, which involved handling the Ising model [a non-sparse Ising model with O(p²) parameters] by an auxiliary representation due to Marc Kac and getting rid of the normalising (partition) constant by the way. (Warning, some approximations involved!) And who showed me a simple probit example of the Gibbs sampler getting stuck as the sample size n grows. Simply because the uniform conditional distribution on the parameter concentrates faster (in 1/n) than the posterior (in 1/√n). This does not come as a complete surprise as data augmentation operates in an n-dimensional space. Hence it requires more time to get around. As a side remark [still worth printing!], Maarten dedicated his thesis as “To my favourite random variables , Siem en Fem, and to my normalizing constant, Esther”, from which I hope you can spot the influence of at least two of my book dedications! As I left Amsterdam on Tuesday, I had time for a enjoyable dinner with E-J’s group, an equally enjoyable early morning run [with perfect skies for sunrise pictures!], and more discussions in the department. Including a presentation of the new (delicious?!) Bayesian software developed there, JASP, which aims at non-specialists [i.e., researchers unable to code in R, BUGS, or, God forbid!, STAN] And about the consequences of mixture testing in some psychological experiments. Once again, a fantastic time discussing Bayesian statistics and their applications, with a group of dedicated and enthusiastic Bayesians!Amster12

the mind of a con man

Posted in University life with tags , , , , , , , on May 21, 2013 by xi'an

“The tone of his talks, he said, was “Let’s not talk about the plumbing, the nuts and bolts — that’s for plumbers, for statisticians.””

As I got a tablet last week and immediately subscribed to the New York Times, I started reading papers from recent editions and got to this long article of April 26, by Yudhijit Bhattacharjee on Diederik Stapel, the Dutch professor of psychology who used fake data in dozens of papers and PhD theses.

“In his early years of research — when he supposedly collected real experimental data — Stapel wrote papers laying out complicated and messy relationships between multiple variables. He soon realized that journal editors preferred simplicity.”

This article is rather puzzling in its presentation of the facts. While Stapel acknowledges making up the data that conveniently supported his theses, the journalist’s analysis is fairly ambivalent, for instance considering that faking data is a “lesser threat to the integrity of science than the massaging of data and selective reporting of experiments”. At the beginning of the article, Stapel is shown going back to places where his experiments were supposed to have taken place, but he “could not find a location that matched the conditions described in his experiment”, making it sound as if he had forgotten…

“Science is of course about discovery, about digging to discover the truth. But it is also communication, persuasion, marketing (…) People are on the road with their talk. With the same talk. It’s like a circus (…) They give a talk in Berlin, two days later they give the same talk in Amsterdam, then they go to London. They are traveling salesmen selling their story.”

The above quote from Stapel is even more puzzling, as if giving the same talk in different places is an unacceptable academic behaviour, in par with faking data and plagiarism… I do give the same talk in several conferences and seminars, mostly to different people and I do not see a problem with this. If I persist in this behaviour, it will get boring to people who see the same talk over and over, and it should lead to me not being invited to conferences or seminars any longer, but there is nothing unethical or a-scientific in this. Another illustration of the ambivalence of both the character and the article. I frankly dislike this approach to fraud, a kind of “50 shades of lies”, where all academics get under suspicion that one way or another they also acted un-ethically and in their own interest rather than towards the advancement of Science…

The case of Lucia de Berk

Posted in Statistics, University life with tags , , , , on September 8, 2010 by xi'an

The posting of a paper by Richard Gill, Piet Groeneboom, and Peter de Jong on arXiv today reminded me of a conference of Richard Gill in Ottawa two years ago where he vehemently defended the Dutch nurse Lucia de Berk. (She has been exonerated from all murder accusation this year, after spending several years in jail.) The current paper gives a very simple explanation of the lack of strong (statistical) evidence against this nurse, which makes the earlier conviction based solely on statistical arguments the more puzzling. (As in earlier cases, the fact that the statistical arguments were delivered by a non-statistician is also very surprising, This shows that judges should both get some basic training in Statistics, rather than considering forbidding statistical argument in court, which I think also is the position of the French courts, and that they should involve statisticians as experts.)