Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4497125 | Journal of Theoretical Biology | 2011 | 9 Pages |
Abstract
Individual based models (IBMs) and Agent based models (ABMs) have become widely used tools to understand complex biological systems. However, general methods of parameter inference for IBMs are not available. In this paper we show that it is possible to address this problem with a traditional likelihood-based approach, using an example of an IBM developed to describe the spread of chytridiomycosis in a population of frogs as a case study. We show that if the IBM satisfies certain criteria we can find the likelihood (or posterior) analytically, and use standard computational techniques, such as MCMC, for parameter inference.
Keywords
Related Topics
Life Sciences
Agricultural and Biological Sciences
Agricultural and Biological Sciences (General)
Authors
Leah R. Johnson, Cheryl J. Briggs,