Search for dissertations about: "Locally Stationary Processes"
Showing result 1 - 5 of 8 swedish dissertations containing the words Locally Stationary Processes.
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1. Modelling and Inference using Locally Stationary Processes : Biomedical applications
Abstract : This thesis considers statistical methods for non-stationary signals, specifically stochastic modelling, inference on the model parameters and optimal spectral estimation. The models are based on Silverman’s definition of Locally Stationary Processes (LSPs). READ MORE
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2. Numerical analysis for random processes and fields and related design problems
Abstract : In this thesis, we study numerical analysis for random processes and fields. We investigate the behavior of the approximation accuracy for specific linear methods based on a finite number of observations. Furthermore, we propose techniques for optimizing performance of the methods for particular classes of random functions. READ MORE
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3. Stochastic systems with locally defined dynamics
Abstract : We study three different classes of models of stochastic systems with locally defined dynamics. Our main points of interest are the limiting properties and convergence in these models. The first class is the locally interactive sequential adsorption, or LISA, models. READ MORE
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4. Predator responses to non-stationary rodent cycles
Abstract : Regular fluctuations in population size, cycles, are common in small mammals and have important effects on predator populations and life histories. In this thesis, I identify long-term patterns and processes in two specialist predators, the arctic fox Vulpes lagopus and the rough-legged buzzard Buteo lagopus, in relation to their prey (lemmings and voles) and in the case of the arctic fox also to a dominant competitor, the red fox Vulpes vulpes. READ MORE
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5. Predictability in Equity Markets: Estimation and Inference
Abstract : The thesis consists of three chapters dealing with predictability in equity markets. The first chapter analyses predictive regressions in a predictive system framework, where the predictor is an imperfect proxy for the expected returns. READ MORE