A study of MCMC and deterministic approximations for hypothesis testing using ODE models
author:
Vladislav Vyshemirsky,
University of Glasgow
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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