Approximate Bayesian computation for parameter inference and model selection in systems biology
In this thesis we present a novel algorithm for parameter estimation and model selection of dynamical systems. The algorithm belongs to the class of approximate Bayesian computation (ABC) methods, which can evaluate posterior distributions without having to calculate likelihoods. It is based on a se...
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Imperial College London
2010
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516970 |