reliable ABC model choice via random forests

October 28, 2014
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(This article was first published on Xi'an's Og R, and kindly contributed to R-bloggers)

human_ldaAfter a somewhat prolonged labour (!), we have at last completed our paper on ABC model choice with random forests and submitted it to PNAS for possible publication. While the paper is entirely methodological, the primary domain of application of ABC model choice methods remains population genetics and the diffusion of this new methodology to the users is thus more likely via a media like PNAS than via a machine learning or statistics journal.

When compared with our recent update of the arXived paper, there is not much different in contents, as it is mostly an issue of fitting the PNAS publication canons. (Which makes the paper less readable in the posted version [in my opinion!] as it needs to fit the main document within the compulsory six pages, relegated part of the experiments and of the explanations to the Supplementary Information section.)

Filed under: pictures, R, Statistics, University life Tagged: 1000 Genomes Project, ABC, ABC model choice, machine learning, model posterior probabilities, posterior predictive, random forests, summary statistics

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