467 citations · 1.2k across the 12 of their papers we have counts for
13 papers
Regression approaches for Approximate Bayesian Computation
Michael GB Blum
This book chapter introduces regression approaches and regression adjustment for Approximate Bayesian Computation (ABC). Regression adjustment adjusts parameter values after reject…
Goodness-of-fit statistics for approximate Bayesian computation
Louisiane Lemaire, Flora Jay, I-Hung Lee +2
Approximate Bayesian computation is a statistical framework that uses numerical simulations to calibrate and compare models. Instead of computing likelihood functions, Approximate…
Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data
Nicolas Duforet-Frebourg, Keurcien Luu, Guillaume Laval +2
To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural select…
Genome scans for detecting footprints of local adaptation using a Bayesian factor model
N. Duforet-Frebourg, E. Bazin, M. G. B. Blum
A central part of population genomics consists of finding genomic regions implicated in local adaptation. Population genomic analyses are based on genotyping numerous molecular mar…
Diagnostic tools of approximate Bayesian computation using the coverage property
D. Prangle, M. G. B. Blum, G. Popovic +1
Approximate Bayesian computation (ABC) is an approach for sampling from an approximate posterior distribution in the presence of a computationally intractable likelihood function.…
Non-stationary patterns of isolation-by-distance: inferring measures of local genetic differentiation with Bayesian kriging
Nicolas Duforet-Frebourg, Michael G. B. Blum
Patterns of isolation-by-distance arise when population differentiation increases with increasing geographic distances. Patterns of isolation-by-distance are usually caused by loca…