Calibration and evaluation of individual-based models using Approximate Bayesian Computation

Elske van der Vaart, Mark A. Beaumont, Alice S.A. Johnston and Richard M. Sibly

Ecological Modelling, 2015, vol. 312, issue C, 182-190

Abstract: This paper investigates the feasibility of using Approximate Bayesian Computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain.

Keywords: Approximate Bayesian Computation; Parameter estimation; Model selection; Individual-based models; Population dynamics (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:312:y:2015:i:c:p:182-190

DOI: 10.1016/j.ecolmodel.2015.05.020

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