A study of MCMC and deterministic approximations for hypothesis testing using ODE models

author: Vladislav Vyshemirsky, Department of Computing Science, University of Glasgow
published: Nov. 6, 2007,   recorded: September 2007,   views: 210

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Description

In this talk we present a comparison of different methods of testing alternative hypotheses expressed using ODE models of biological systems.

We investigated applicability, limitations and stability of a range of hypotheses testing methods including maximum likelihood based information criteria, local deterministic approximations around maximum a posteriori estimates (Laplace approximations) for computing marginal likelihoods, importance sampling based marginal likelihood estimators, and a path sampling estimator built upon the principles of thermodynamic integration.

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