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Department of Life Sciences
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Department of Physics
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Department of Electrical and Electronic Engineering
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    ABSTRACT: A system to update estimates from a sequence of probability distributions is presented. The aim of the system is to quickly produce estimates with a user-specified bound on the Monte Carlo error. The estimates are based upon weighted samples stored in a database. The stored samples are maintained such that the accuracy of the estimates and quality of the samples are satisfactory. This maintenance involves varying the number of samples in the database and updating their weights. New samples are generated, when required, by a Markov chain Monte Carlo algorithm. The system is demonstrated using a football league model that is used to predict the end of season table. The correctness of the estimates and their accuracy are shown in a simulation using a linear Gaussian model.
    Computational Statistics & Data Analysis 12/2014; 80:99–110.
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    ABSTRACT: This work addresses the topic of constrained dynamic programming for problems involving multi-stage mixed-integer linear formulations with a linear objective function. It is shown that such problems may be decomposed into a series of multi-parametric mixed-integer linear problems, of lower dimensionality, that are sequentially solved to obtain the globally optimal solution of the original problem. At each stage, the dynamic programming recursion is reformulated as a convex multi-parametric programming problem, therefore avoiding the need for global optimisation that usually arises in hard constrained problems. The proposed methodology is applied to a problem of mixed-integer linear nature that arises in the context of inventory scheduling. The example also highlights how the complexity of the original problem is reduced by using dynamic programming and multi-parametric programming.
    Computers & Chemical Engineering 11/2014;
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    ABSTRACT: Quasi-static finite element analysis; Seismic design of tunnels; Equivalent linear site response analysis
    Soil Dynamics and Earthquake Engineering 11/2014; 66:206-219.


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    South Kensington Campus, London, SW7 2AZ, London, United Kingdom
  • Head of Institution
    Sir Keith O’Nions
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C.E.P.R. Discussion Papers, CEPR Discussion Papers. 01/2001;
The Economic Journal 07/2008; 118(531):1223 - 1244.

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