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Activity Number: 495
Type: Invited
Date/Time: Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract - #303230
Title: Approximate Bayesian Computation: What, Why, and When?
Author(s): Simon Tavare*+
Companies: University of Southern California
Address: Program in Molecular and Computational Biology, Los Angeles, CA, 90089-2910,
Keywords: MCMC ; ABC ; sufficiency ; Bayesian inference

Approximate Bayesian Computation (ABC) provides a computationally cheap method for approximating posterior distributions coming from complex stochastic models for which likelihoods are hard or impossible to compute. In this talk I will describe some variants on the ABC theme, illustrate what we know about the performance of the methods, and outline a number of unsolved aspects of the theory. Some applications to inference in the fossil record and to the evolutionary history of tumors will also be described.

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Revised September, 2008