articleAnnual Review of Ecology Evolution and SystematicsNov 2, 2010Closed access

Approximate Bayesian Computation in Evolution and Ecology

University of Bristol

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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…

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Topics & keywords

Keywords
  • Approximate Bayesian computation
  • Divergence (linguistics)
  • Bayesian probability
  • Computer science
  • Computation
  • Population
  • Bayes' theorem
  • Ecology
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