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• W2167030304 endingPage "406" @default.
• W2167030304 startingPage "379" @default.
• W2167030304 abstract "In the past 10years a statistical technique, approximate Bayesian computation (ABC), has been developed that can be used to infer parameters and choose between models in the complicated scenarios that are often considered in the environmental sciences. For example, based on gene sequence and microsatellite data, the method has been used to choose between competing models of human demographic history as well as to infer growth rates, times of divergence, and other parameters. The method fits naturally in the Bayesian inferential framework, and a brief overview is given of the key concepts. Three main approaches to ABC have been developed, and these are described and compared. Although the method arose in population genetics, ABC is increasingly used in other fields, including epidemiology, systems biology, ecology, and agent-based modeling, and many of these applications are briefly described." @default.
• W2167030304 created "2016-06-24" @default.
• W2167030304 creator A5018479163 @default.
• W2167030304 date "2010-12-01" @default.
• W2167030304 modified "2023-10-13" @default.
• W2167030304 title "Approximate Bayesian Computation in Evolution and Ecology" @default.
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