Search for dissertations about: "variance estimators"
Showing result 16 - 20 of 46 swedish dissertations containing the words variance estimators.
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16. Recent Studies on Lp-Norm Estimation
Abstract : When estimating the parameters in a linear regression model, the method of least squares (L^-norm estimator) is often used. When thè residuals are independent and identically normally distributed, the least squares estimator is BLUE as well as equivalent to the maximum likelihood estimator. READ MORE
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17. Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
Abstract : This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. READ MORE
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18. Issues of multicollinearity and conditional heteroscedasticy in time series econometrics
Abstract : This doctoral thesis consists of four chapters all related to the field of time series econometrics. The main contribution is firstly the development of robust methods when testing for Granger causality in the presence of generalized autoregressive conditional heteroscedasticity (GARCH) and causality-in-variance (i.e. spillover) effects. READ MORE
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19. Computerized achievement tests : sequential and fixed length tests
Abstract : The aim of this dissertation is to describe how a computerized achivement test can be constructed and used in practice. Throughout this dissertation the focus is on classifying the examinees into masters and non-masters depending on their ability. However, there has been no attempt to estimate their ability. READ MORE
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20. Discrete Stochastic Time-Frequency Analysis and Cepstrum Estimation
Abstract : The theory of stochastic time-frequency analysis of non-stationary random processes has mostly been developed for processes in continuous time. In practice however, random processes are observed, processed, and interpreted at a finite set of time points. READ MORE