Search for dissertations about: "examples of non probability of sampling"
Showing result 1 - 5 of 9 swedish dissertations containing the words examples of non probability of sampling.
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1. Estimation of the reliability of systems described by the Daniels Load-Sharing Model
Abstract : We consider the problem of estimating the failure stresses of bundles (i.e. the tensile forces that destroy the bundles), constructed of several statisti-cally similar fibres, given a particular kind of censored data. READ MORE
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2. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors
Abstract : The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. READ MORE
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3. Quantization of Random Processes and Related Statistical Problems
Abstract : In this thesis we study a scalar uniform and non-uniform quantization of random processes (or signals) in average case setting. Quantization (or discretization) of a signal is a standard task in all nalog/digital devices (e.g., digital recorders, remote sensors etc. READ MORE
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4. Statistical analysis and simulation methods related to load-sharing models
Abstract : We consider the problem of estimating the reliability of bundles constructed of several fibres, given a particular kind of censored data. The bundles consist of several fibres which have their own independent identically dis-tributed failure stresses (i.e.the forces that destroy the fibres). READ MORE
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5. Machine learning with state-space models, Gaussian processes and Monte Carlo methods
Abstract : Numbers are present everywhere, and when they are collected and recorded we refer to them as data. Machine learning is the science of learning mathematical models from data. Such models, once learned from data, can be used to draw conclusions, understand behavior, predict future evolution, and make decisions. READ MORE