[Here is a revised version of my comments on the paper by Julien Stoehr, Pierre Pudlo, and Lionel Cucala, now to appear [both paper and comments] in Statistics and Computing special MCMSki 4 issue.] Approximate Bayesian computation techniques are 2000’s successors of MCMC methods as handling new models where MCMC algorithms are at a loss, […]
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insufficient statistics for ABC model choice
October 17, 2014insufficient statistics for ABC model choice
February 12, 2014Julien Stoehr, Pierre Pudlo, and Lionel Cucala (I3M, Montpellier) arXived yesterday a paper entitled “Geometric summary statistics for ABC model choice between hidden Gibbs random fields“. Julien had presented this work at the MCMski 4 poster session. The move to a hidden Markov random field means that our original approach with Aude Grelaud does not […]
ABC and sufficient statistics
July 8, 2011Chris Barnes, Sarah Filippi, Michael P.H. Stumpf, and Thomas Thorne posted a paper on arXiv on the selection of sufficient statistics towards ABC model choice. This paper, called Considerate Approaches to Achieving Sufficiency for ABC model selection, was presented by Chris Barnes during ABC in London two months ago. (Note that all talks of the meeting […]
Sufficient statistics for ABC
November 20, 2008The issue of picking quasi-sufficient statistics in ABC algorithms is quite important and Joyce and Marjoram have published (last August, sorry I’m late!) a proposal in Statistical Applications in Genetics and Molecular Biology that is addressing this issue, at least to the extend that the inclusion of a new statistics within the set of summary […]
ABC with inflated tolerance
December 8, 2020For the last One World ABC seminar of the year 2020, this coming Thursday, Matti Vihola is speaking from Finland on his recent Biometrika paper “On the use of ABC-MCMC with inflated tolerance and post-correction”. To attend the talk, all is required is a registration on the seminar webpage. The Markov chain Monte Carlo (MCMC) […]
