Geodesic
An overview on Approximate Bayesian computation
Meïli Baragatti1 ; Pierre Pudlo2, 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
ESAIM. Proceedings, Tome 44 (2014), pp. 291-299 Cet article a éte moissonné depuis la source EDP Sciences

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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.
DOI : 10.1051/proc/201444018

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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%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

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