Posts Tagged ‘ Read paper ’

Large-scale Inference

February 23, 2012
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Large-scale Inference

Large-scale Inference by Brad Efron is the first IMS Monograph in this new series, coordinated by David Cox and published by Cambridge University Press. Since I read this book immediately after Cox’ and Donnelly’s Principles of Applied Statistics, I was thinking of drawing a parallel between the two books. However, while none of them can

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recents advances in Monte Carlo Methods

February 8, 2012
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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 Lee, Warwick University, Auxiliary variables and many-core

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semi-automatic ABC

December 17, 2011
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semi-automatic ABC

The talk of Wednesday afternoon Ordinary Meeting of the Royal Statistical Society went on quite well, I think. I would have expected a few people (in general) and some specific people (in particular) but this being the last week of term the schedule was not the best of times. Paul Fearnhead gave the talk, insisting

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Catching up faster by switching sooner

October 25, 2011
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Catching up faster by switching sooner

Here is our discussion (with Nicolas Chopin) of the Read Paper of last Wednesday by T. van Erven, P. Grünwald and S. de Rooij (Centrum voor Wiskunde en Informatica, Amsterdam), entitled Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the Akaike information criterion–Bayesian information criterion dilemma. It

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Riemann, Langevin & Hamilton [reply]

September 27, 2010
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Riemann, Langevin & Hamilton [reply]

Here is a (prompt!) reply from Mark Girolami corresponding to the earlier post: In preparation for the Read Paper session next month at the RSS, our research group at CREST has collectively read the Girolami and Calderhead paper on Riemann manifold Langevin and Hamiltonian Monte Carlo methods and I hope we will again produce a

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