This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 222
Type: Topic Contributed
Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #306753
Title: Bayesian Model Comparison in Cosmology with Population Monte Carlo
Author(s): Christian Plessis Robert*+
Companies: Universite Paris-Dauphine
Address: CEREMADE, Paris cedex 16, International, 75775, France
Keywords: Bayesian model choice ; hypothesis testing ; population Monte Carlo ; evidence

We use Bayesian model selection techniques to test extensions of the standard flat paradigm. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulation and from data. For our cases, the log-evidence is calculated with a precision of 0.08.

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