Blog Archives

Postdoc in Wharton

November 16, 2010
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Postdoc in Wharton

Just received this email from José Bernardo about an exciting postdoc position in Wharton: POST-DOCTORAL FELLOW – DEPARTMENT OF STATISTICS, THE WHARTON SCHOOL The Department of Statistics at The Wharton School of the University of Pennsylvania is seeking candidates for a Post-Doctoral Fellowship. This research fellowship provides full funding without any teaching requirements at a

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Introducing Monte Carlo in PaRis

November 14, 2010
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Introducing Monte Carlo in PaRis

As already announced on Statisfaction, I will start a short course in English based on Introducing Monte Carlo Methods with R at ENSAE next Tuesday. The slides were written by George Casella for a course he gave in Italy last spring and he kindly agreed on making them available on slideshare: Filed under:

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Bayesian Inference for Latent Gaussian Models

November 12, 2010
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Bayesian Inference for Latent Gaussian Models

An exciting conference in Zurich next February, 02-05. (I think I will attend! And not for skiing reasons!) Latent Gaussian models have numerous applications, for example in spatial and spatio-temporal epidemiology and climate modelling. This workshop brings together researchers who develop and apply Bayesian inference in this broad model class. One methodological focus is on

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Particle learning [rejoinder]

November 9, 2010
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Particle learning [rejoinder]

Following the posting on arXiv of the Statistical Science paper of Carvalho et al., and the publication by the same authors in Bayesian Analysis of Particle Learning for general mixtures I noticed on Hedibert Lopes’ website his rejoinder to the discussion of his Valencia 9 paper has been posted. Since the discussion involved several points

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Computational position in Texas

November 8, 2010
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Computational position in Texas

José Bernardo forwaded this announcement that sounds quite attractive (conditional upon living in a remote part of Texas!) Senior Faculty Position in Computational Statistics At Texas A&M University As part of a recognition of the increasing importance in the modeling and computational sciences, the Department of Statistics at Texas A&M University is recruiting for a

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Le Monde puzzle [43]

November 7, 2010
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Le Monde puzzle [43]

Here is the puzzle in Le Monde I missed last week: Given a country with 6 airports and a local company with three destinations from each of the six airports, is it possible to find a circular trip with three intermediate stops from one of the airports? From all of the airports? One more airport

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ABC lectures [finale]

October 31, 2010
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ABC lectures [finale]

The latest version of my ABC slides is on slideshare. To conclude with a pun, I took advantage of the newspaper clipping generator once pointed out by Andrew. (Note that nothing written in the above should be taken seriously.) On the serious side, I managed to cover most of the 300 slides (!) over the

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Random generators for parallel processing

October 28, 2010
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Random generators for parallel processing

Given the growing interest in parallel processing through GPUs or multiple processors, there is a clear need for a proper use of (uniform) random number generators in this environment. We were discussing the issue yesterday with Jean-Michel Marin and briefly looked at a few solutions: given p parallel streams/threads/processors, starting each generator with a random

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Le Monde puzzle [42]

October 24, 2010
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Le Monde puzzle [42]

An interesting suduko-like puzzle for this week puzzle in Le Monde thi A 10×10 grid is filled by a random permutation of {0,…,99}. The 4 largest figures in each row are coloured in yellow and the 4 largest values in each column are coloured in red. What is the range of the number of yellow-and-red

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abc

October 21, 2010
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abc

Michael Blum and Olivier François, along with Katalin Csillery, just released an R package entitled abc. (I am surprised the name was not already registered!) Its aim is obviously to implement ABC approximations for Bayesian inference: Description The ’abc’ package provides various functions for parameter estimation and model selection in an ABC framework. Three main

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