Archive for support


Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , on October 9, 2018 by xi'an

The next BNP (Bayesian nonparametric) conference is taking place in Oxford (UK), prior to the O’Bayes 2019 conference in Warwick, in June 24-28 and June 29-July 2, respectively. At this stage, the Scientific Committee of BNP12 invites submissions for possible contributed talks. The deadline for submitting a title/abstract is 15th December 2018. And the submission of applications for travel support closes on 15th December 2018. Currently, there are 35 awards that could be either travel awards or accommodation awards. The support is for junior researchers (students currently enrolled in a Dphil (PhD) programme or having graduated after 1st October 2015). The applicant agrees to present her/his work at the conference as a poster or oraly if awarded the travel support.

As for O’Bayes 2019, we are currently composing the programme, following the 20 years tradition of these O’Bayes meetings of having the Scientific Committee (Marilena Barbieri, Ed George, Brunero Liseo, Luis Pericchi, Judith Rousseau and myself) inviting about 25 speakers to present their recent work and 25 discussants to… discuss these works. With a first day of introductory tutorials to Bayes, O’Bayes and beyond. I (successfully) proposed this date and location to the O’Bayes board to take advantage of the nonparametric Bayes community present in the vicinity so that they could attend both meetings at limited cost and carbon impact.

prior against truth!

Posted in Books, Kids, Statistics with tags , , , , , , , on June 4, 2018 by xi'an

A question from X validated had interesting ramifications, about what happens when the prior does not cover the true value of the parameter (assuming there ? In fact, not so much in that, from a decision theoretic perspective, the fact that that π(θ⁰)=0, or even that π(θ)=0 in a neighbourhood of θ⁰ does not matter [too much]. Indeed, the formal derivation of a Bayes estimator as minimising the posterior loss means that the resulting estimator may take values that were “impossible” from a prior perspective! Indeed, taking for example the posterior mean, the convex combination of all possible values of θ under π may well escape the support of π when this support is not convex. Of course, one could argue that estimators should further be restricted to be possible values of θ under π but that would reduce their decision theoretic efficiency.

An example is the brilliant minimaxity result by George Casella and Bill Strawderman from 1981: when estimating a Normal mean μ based on a single observation xwith the additional constraint that |μ|<ρ, and when ρ is small enough, ρ1.0567 quite specifically, the minimax estimator for this problem under squared error loss corresponds to a (least favourable) uniform prior on the pair {ρ,ρ}, meaning that π gives equal weight to ρ and ρ (and none to any other value of the mean μ). When ρ increases above this bound, the least favourable prior sees its support growing one point at a time, but remaining a finite set of possible values. However the posterior expectation, 𝔼[μ|x], can take any value on (ρ,ρ).

In an even broader suspension of belief (in the prior), it may be that the prior has such a restricted support that it cannot consistently estimate the (true value of the) parameter, but the associated estimator may remain admissible or minimax.

humanitarian project in Madagascar

Posted in Books, Kids, pictures, Travel, University life with tags , , , , , , , , , on March 15, 2017 by xi'an

As the budget of the humanitarian trip to Madagascar our daughter organises with other students of the Paris-Sud Medical School next summer is still short of several thousand euros, I repost the call for support I made a few months ago.

Their project is called Mada Tsatsaka, mada for Madagascar and tsatsaka for a local lizard. The team plans to bring basic drugs and educational material and to work in a dispensary, an orphanage, as well as a shelter for women victims of violence. (More below!)

I thus bring this project to the ‘Og’s readers’ attention in case they wish to support. The best approach is use this web site for donations (in English) to Evadeh Mada Tsatsaka. (Evadeh is the mother association for all humanitarian projects in the medical school.) A free-of-charge (!) alternative is to shop on following this associate link as I vouch to transfer all my associate gains in the next four months to the project.

Upon request, more details on the project:

  • 2 weeks in Maventibao working in a clinic : Mada Clinics, helping two nurses with free medical examinations and providing extra medical equipment and drugs. And also helping with drinking water improvement. The team further hopes to help with the purchase of a car associated with the clinic and linking with the hospital in  Diego (4h away) and with hiring a doctor in the nearby clinic of Amboangamamy.
  • 2 weeks in an orphanage in Antananarivo, Ankanifitahiana, in collaboration with BLOC Léo Madagascar, helping in financing and installing a library and a music room, and participating in classes and games with the children. Depending on the funding, the team would also like to help with installing a solar oven.

Special postdoctoral positions in Paris

Posted in Statistics, University life with tags , , on November 7, 2008 by xi'an

The Foundation Sciences Mathématiques de Paris offers fifteen (15) post-doctoral positions in mathematics and in computer science. These positions last one year (renewable once) and are to be filled as from October 1, 2009, in the research laboratories affiliated to the Foundation.” This means that postdocs interested in a year of study in Paris 6, Paris 7, ENS Ulm or, who knows?, Dauphine, should apply there as the financial support is much better than the French standards. The requirements, beside holding a PhD degree, are almost nil. Enquiries and requests for details are to be made to the contacts indicated on the webpage, not to me. Unless of course one is interested in working with me on Bayesian model choice and adaptive Monte Carlo.