[Ml-stat-talks] christian robert speaks about ABC on tuesday april 3

David Blei blei at CS.Princeton.EDU
Fri Mar 30 08:26:41 EDT 2012

hi ml-stat-talks

christian robert is speaking on tuesday about ABC and model selection.
 i've pasted the abstract below my signature.

the talk is in the economics department, in their econometrics seminar:

2:40 - 4:00pm
200 Fisher Hall

also see




"Approximate Bayesian Computation and consistent model selection"

Approximate Bayesian computation (ABC), also known as likelihood-free
methods, has become a standard tool for the analysis of complex
models, primarily in population genetics but also for complex
financial models.

The development of new ABC methodology is undergoing a rapid increase
in the past years, as shown by multiple publications, conferences and
even softwares. While one valid interpretation of ABC based estimation
is connected with nonparametrics, the setting is quite different for
model choice issues. We examined in Grelaud et al. (BA, 2009) the use
of ABC for Bayesian model choice in the specific of Gaussian random
fields (GRF), relying on a sufficient property to show that the
approach was legitimate.

Despite having previously suggested the use of ABC for model choice in
a wider range of models in the DIY ABC software (Cornuet et al.,
2008), we present in Robert et al. (PNAS, 2011) theoretical evidence
that the general use of ABC for model choice is fraught with danger in
the sense that no amount of computation, however large, can guarantee
a proper approximation of the posterior probabilities of the models
under comparison. In a more recent work (Marin et al., 2011), we
expand on this warning to derive necessary and sufficient conditions
on the choice of summary statistics for ABC model choice to be
asymptotically consistent.

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