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machine learning methods are useful for ABC [or my first PCI Evol Biol!]

November 23, 2017

While I am still working on setting a PCI [peer community in] Comput Stats, having secure sponsorship of some societies (ASA, KSS, RSS, SFdS, and hopefully ISBA), my coauthors Jean-Michel Marin and Louis Raynal submitted our paper ABC random forests for Bayesian parameter inference to PCI Evol Biol. And after a few months of review, […]

lazy ABC…what?!

November 8, 2017

running ABC when the likelihood is available

September 19, 2017

Today I refereed a paper where the authors used ABC to bypass convergence (and implementation) difficulties with their MCMC algorithm. And I am still pondering whether or not this strategy makes sense. If only because ABC needs to handle the same complexity and the same amount of parameters as an MCMC algorithm. While shooting “in […]

model misspecification in ABC

August 21, 2017

With David Frazier and Judith Rousseau, we just arXived a paper studying the impact of a misspecified model on the outcome of an ABC run. This is a question that naturally arises when using ABC, but that has been not directly covered in the literature apart from a recently arXived paper by James Ridgway [that […]

ABC gas

August 9, 2017