Incredibly ugly squalid pictures…
Well, this is not a common teaser to attract readers, but a comment on one of my graphs in the second revision of our paper Adaptivity for approximate Bayesian computation algorithms: a population Monte Carlo approach, written with Marc Beaumont, Jean-Marie Cornuet, and Jean-Michel Marin, and (re-re-)submitted to Biometrika… Not something I’d like to hear about my graphs, thank you!, as the pdf version of the graph on the right actually looks better than that one…. Anyway, we revised the paper towards less squalidness, replacing histogram with density using the “h” type in R. The major request on the revision was to get under eight pages in order to fit inside the Miscelanea section of Biometrika. Changes are thus mostly cosmetic compared with the earlier version, as you can check on the arXiv list of versions. The background for the paper and the earlier paper of Sisson, Fan, and Tanaka (2007, PNAS) it analyses, are described in this earlier post.
February 9, 2012 at 12:13 am
[…] Pommeret, from Luminy, Marseilles. The paper mentions our population Monte Carlo (PMC) algorithm (Beaumont et al., 2009) and other ABC-SMC algorithms, but opts instead for an ABC-MCMC basis. The purpose is to build […]
December 11, 2011 at 12:14 am
[…] by Sarah Filippi, Chris Barnes, Julien Cornebise, and Michael Stumpf, is in the lineage of our 2009 Biometrika ABC-PMC (population Monte Carlo) paper with Marc Beaumont, Jean-Marie Cornuet and Jean-Michel […]
August 20, 2011 at 12:14 am
[…] tuberculosis example of Tanaka et al. (2006, Genetics), the authors report better performances than ABC-PMC, ABC-MCMC and ABC. (In a bimodal toy example, ABC-PMC does not identify a second mode, which […]
July 21, 2010 at 12:11 am
[…] aspects of ABC and on the more adaptive [PMC] features of ABC-SMC, as processed in our Biometrika ABC-PMC paper and in Del Moral, Doucet and Jasra. (Again, this is not a criticism in that the paper got […]