Loading...
Please wait, while we are loading the content...
Similar Documents
Approximate Bayesian Computation 1 Approximate Bayesian Computation in Evolution and Ecology
| Content Provider | Semantic Scholar |
|---|---|
| Author | Beaumont, Mark A. |
| Copyright Year | 2010 |
| Abstract | In the last 10 years 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, and 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 has become increasingly used in other fields, including epidemiology, systems biology, ecology, and agent-based modelling, and many of these applications are briefly described. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://grids.ac.uk/Complex/Leeds.15.6.10/Beaumont_abc.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
