slides for my simulation course

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 Casella. Here … Continue reading

recents advances in Monte Carlo Methods

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 … Continue reading

principles of uncertainty

“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 … Continue reading

Handbook of Markov chain Monte Carlo

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 to get a look at the book until … Continue reading

Terry’s spiel

“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 … Continue reading

Postdoc on adaptive MCMC in Paris

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 … Continue reading

MCMC with errors

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 target … Continue reading

Special issue of TOMACS

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 … Continue reading