Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems.
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ABSTRACT:
SUBMITTER: Toni T
PROVIDER: S-EPMC2658655 | biostudies-literature | 2009 Feb
REPOSITORIES: biostudies-literature
Publications
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems.
Toni Tina T Welch David D Strelkowa Natalja N Ipsen Andreas A Stumpf Michael P H MP
Journal of the Royal Society, Interface 20090201 31
Approximate Bayesian computation (ABC) methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper, we discuss and apply an ABC method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models. We show that ABC SMC provides information about the inferability of parameters and model sensitivity to changes in parameters, and tends to perform better than other ABC approaches. The algorithm is applied to several well-known bio ...[more]
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