1UMR MISTEA, Montpellier SupAgro-INRA, France 2Université Montpellier 2, I3M UMR CNRS 5149, Montpellier, France 3INRA, UMR 1062 CBGP, Montferrier-sur-Lez, France
ESAIM. Proceedings, Tome 44 (2014), pp. 291-299
Cet article a éte moissonné depuis la source EDP Sciences
Approximate Bayesian computation techniques, also called likelihood-free methods, are one of the most satisfactory approach to intractable likelihood problems. This overview presents recent results since its introduction about ten years ago in population genetics.
Meïli Baragatti 
1
;
Pierre Pudlo 
2
,
3
1
UMR MISTEA, Montpellier SupAgro-INRA, France
2
Université Montpellier 2, I3M UMR CNRS 5149, Montpellier, France
3
INRA, UMR 1062 CBGP, Montferrier-sur-Lez, France
@article{EP_2014_44_a18,
author = {Me{\"\i}li Baragatti and Pierre Pudlo},
title = {An overview on {Approximate} {Bayesian} computation},
journal = {ESAIM. Proceedings},
pages = {291--299},
year = {2014},
volume = {44},
doi = {10.1051/proc/201444018},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.1051/proc/201444018/}
}
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AU - Pierre Pudlo
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%J ESAIM. Proceedings
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Meïli Baragatti; Pierre Pudlo. An overview on Approximate Bayesian computation. ESAIM. Proceedings, Tome 44 (2014), pp. 291-299. doi: 10.1051/proc/201444018