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Maximum likelihood parameter estimation in time series models using sequential Monte Carlo
(University of CambridgeDepartment of Pure Mathematics and Mathematical StatisticsStatistical LaboratoryDarwin College, 2013-06-11)
Time series models are used to characterise uncertainty in many real-world dynamical phenomena. A time series model typically contains a static variable, called parameter, which parametrizes the joint law of the random ...
Hidden states, hidden structures: Bayesian learning in time series models
(University of CambridgeDepartment of Engineering, 2014-06-10)
This thesis presents methods for the inference of system state and the learning of model structure for a number of hidden-state time series models, within a Bayesian probabilistic framework. Motivating examples are taken ...