Similar to last year, I am giving a series of lectures on simulation jointly as a Master course in Paris-Dauphine and as a 3rd year course in ENSAE. The course borrows from both the books Monte Carlo Statistical Methods and from Introduction to Monte Carlo Methods with R, with George ... [Read more...]

This is a talk I gave this week in Advanced Biostatistics at McGill. The goal was to provide an gentle introduction to Bayesian methodology and to demonstrate how it is used for inference and prediction. There is a link to an accompanying R script in the slides [Read more...]

Another day full of interesting and challenging—in the sense they generated new questions for me—talks at the SuSTain workshop. After another (dry and fast) run around the Downs; Leo Held started the talks with one of my favourite topics, namely the theory of g-priors in generalized linear models. ... [Read more...]

As advertised on the ‘Og, the ISBA mailing list and now the birth certificate of BayesComp (!), MCMSki IV is taking place for sure in Chamonix-Mont-Blanc, January 6-8 2014. The webpage has been started, thanks to Merrill Liechty, and should grow with informations about the location, the hotels, registration, transportation, and of ... [Read more...]

Monday, March 26, 2012  14h-16h, Stewart Biology N4/17 Corey Chivers, Department of Biology McGill University This is a meetup of the Montreal R User Group. Be sure to join the group and RSVP. More information about the workshop here. Topics Why would we want to be Bayesian in the first place?  ... [Read more...]

Next Thursday (Jan. 16), at the RSS, there will be a special half-day meeting (afternoon, starting at 13:30) on Recent Advances in Monte Carlo Methods organised by the General Application Section. The speakers are Richard Everitt, University of Oxford, Missing data, and what to do about it Anthony Lee, Warwick University, Auxiliary ... [Read more...]

Bill Bolstad wrote a reply to my review of his book Understanding computational Bayesian statistics last week and here it is, unedited except for the first paragraph where he thanks me for the opportunity to respond, “so readers will see that the book has some good features beyond having a “... [Read more...]

“Bayes Theorem is a simple consequence of the axioms of probability, and is therefore accepted by all as valid. However, some who challenge the use of personal probability reject certain applications of Bayes Theorem.“  J. Kadane, p.44 Principles of uncertainty by Joseph (“Jay”) Kadane (Carnegie Mellon University, Pittsburgh) is a ... [Read more...]

I have just finished reading this book by Bill Bolstad (University of Waikato, New Zealand) which a previous ‘Og post pointed out when it appeared, shortly after our Introducing Monte Carlo Methods with R. My family commented that the cover was nicer than those of my own books, which is ... [Read more...]

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At JSM, John Kimmel gave me a copy of the Handbook of Markov chain Monte Carlo, as I had not (yet?!) received it. This handbook is edited by Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng, all first-class jedis of the MCMC galaxy. I had not had a chance ... [Read more...]

“We don’t need likelihood functions; we just need to know how to simulate from [them] (…) We don’t need models with sufficient statistics; we just need summary statistics (…) We don’t need to be Bayesian; we just need to be approximately so. We don’t need theory to tell ... [Read more...]

Although the official deadline is long past, I just became aware of this call for a postdoctoral position in Paris starting next Fall. Please feel free to apply: Summary Adaptive Markov Chain Monte Carlo (MCMC) methods are currently a very active field of research. MCMC methods are sampling methods, based ... [Read more...]

I received this email last week from Ian Langmore, a postdoc in Columbia: I’m looking for literature on a subject and can’t find it:  I have a Metropolis sampler where the acceptance probability is evaluated with some error.  This error is not simply error in evaluation of the ... [Read more...]

TOMACS (ACM Transactions on Modeling and Computer Simulation) is launching a call for paper submission. The special topic is Monte Carlo Methods in Statistics and Arnaud Doucet and myself are the special issue editors. Here are the details.: Over the last two decades Monte Carlo methods have attracted much attention ... [Read more...]

The paper “Exact sampling for intractable probability distributions via a Bernoulli factory” by James Flegal and Radu Herbei got posted on arXiv without me noticing, presumably because it came out just between Larry Brown’s conference in Philadelphia and my skiing vacations! I became aware of it only yesterday and ... [Read more...]

An announcement for two short-courses on Introduction to  Bayesian Analysis and MCMC, and Hierarchical Modelling of Spatial and Temporal Data by Alan Gelfand (Duke University, USA) and Sujit Sahu (University of Southampton, UK), are to take place in Southampton on June 7-10, this year. Course 1: Introduction to Bayesian Analysis and ... [Read more...]

While the above heading sounds like a title in reverse, its words are in the “correct” order in that our paper with George Casella, A Short History of Markov Chain Monte Carlo, has been accepted for publication by Statistical Science. This publication may sound weird when considering that the paper ... [Read more...]

Here is the poster presented at MCMSki III next week by Pierre Jacob about our joint paper on parallelisation: Filed under: R, Statistics, Travel Tagged: Adapski, MCMC, MCMSki, Metropolis-Hastings, Monte Carlo Statistical Methods, parallelisation, pos... [Read more...]

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