Search for dissertations about: "Mathematical Statistics"
Showing result 6 - 10 of 263 swedish dissertations containing the words Mathematical Statistics.
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6. 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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7. Four applications of stochastic processes : Contagious disease, credit risk, gambling and bond portfolios
Abstract : This thesis consists of four papers on applications of stochastic processes. In Paper I we study an open population SIS (Susceptible - Infective - Susceptible) stochastic epidemic model from the time of introduction of the disease, through a possible outbreak and to extinction. The analysis uses coupling arguments and diffusion approximations. READ MORE
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8. Regression methods in multidimensional prediction and estimation
Abstract : In regression with near collinear explanatory variables, the least squares predictor has large variance. Ordinary least squares regression (OLSR) often leads to unrealistic regression coefficients. Several regularized regression methods have been proposed as alternatives. READ MORE
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9. Stochastic claims reserving in non-life insurance : Bootstrap and smoothing models
Abstract : In practice there is a long tradition of actuaries calculating reserve estimates according to deterministic methods without explicit reference to a stochastic model. For instance, the chain-ladder was originally a deterministic reserving method. READ MORE
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10. Toward Sequential Data Assimilation for NWP Models Using Kalman Filter Tools
Abstract : The aim of the meteorological data assimilation is to provide an initial field for Numerical Weather Prediction (NWP) and to sequentially update the knowledge about it using available observations. Kalman filtering is a robust technique for the sequential estimation of the unobservable model state based on the linear regression concept. READ MORE