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Likelihood-Free Inference in High-Dimensional Models

Methods that bypass analytical evaluations of the likelihood function have become an indispensable tool for statistical inference in many fields of science. These so-called likelihood-free methods rely on accepting and rejecting simulations based on summary statistics, which limits them to low-dimen...

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Publicat a:Genetics
Autors principals: Kousathanas, Athanasios, Leuenberger, Christoph, Helfer, Jonas, Quinodoz, Mathieu, Foll, Matthieu, Wegmann, Daniel
Format: Artigo
Idioma:Inglês
Publicat: Genetics Society of America 2016
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC4896201/
https://ncbi.nlm.nih.gov/pubmed/27052569
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1534/genetics.116.187567
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