approximate bayesian computation thesis

In this project probabilistic algorithms (e.g. MCMC) will be applied together with a relatively recent Bayesian methodology, named ABC (approximate Bayesian computation). ABC comes as a powerful tool allowing for Bayesian inference in situations where the likelihood function is unavailable or is expensive to evaluate.
09.08.2014 -
This thesis presents the development of a new numerical algorithm for statistical in- ference problems that require sampling from distributions which are intractable. We propose to develop our sampling algorithm based on a class of Monte Carlo meth- ods, Approximate Bayesian Computation (ABC), which are specifically
... APPLICATION OF APPROXIMATE BAYESIAN COMPUTATION IN. THE CALIBRATION OF HYDROLOGICAL MODELS by. Jason John Brown. A thesis submitted in partial fulfillment of the requirements for the degree of. Master of Science. In. Land Resources and Environmental Sciences. MONTANA STATE UNIVERSITY.
UNIVERSITY OF SOUTHAMPTON. FACULTY OF PHYSICAL SCIENCES AND ENGINEERING. Electronics and Computer Science. Fast approximate Bayesian computation for inference in non-linear differential equations by. Sanmitra Ghosh. Thesis for the degree of Doctor of Philosophy. September 2016
free” techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo
08.12.2009 -
26.08.2014 -
With increasing model complexity, sampling from the posterior distribution in a Bayesian context becomes challenging. The reason might be that the likelihood function is analytically unavailable or computationally costly to evaluate. In this thesis a fairly new scheme called approximate Bayesian computation is studied
Approximate Bayesian computation for parameter inference and model selection in systems biology by. Tina Toni. Division of Molecular Biosciences, Imperial College London. A thesis submitted for the degree of. Doctor of Philosophy of the University of London. February 2010

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