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T1 - Fundamentals and Recent Developments in Approximate Bayesian Computation
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UR - http://hdl.handle.net/10138/312716
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A1 - Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka
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Y1 - 2017
LA - eng
AB - Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by o...
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KW - ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models; MONTE-CARLO; INDIRECT INFERENCE; MODEL SELECTION; EVOLUTION; LIKELIHOODS; SYSTEMS; STATISTICS; PARAMETERS; 1181 Ecology, evolutionary biology; 112 Statistics and probability
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