Search for dissertations about: "Thomas Holgersson"
Showing result 6 - 10 of 17 swedish dissertations containing the words Thomas Holgersson.
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6. Aspects of common principal components
Abstract : The focus of this thesis is the common principal component (CPC) model, the generalization of principal components to several populations. Common principal components refer to a group of multidimensional datasets such that their inner products share the same eigenvectors and are therefore simultaneously diagonalized by a common decorrelator matrix. READ MORE
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7. Local Influence Analysis and Cross-over Studies
Abstract : With a special reference to cross-over design models with random individual effects, the purpose of this dissertation is to develop new methodology to detect influential observations in the context of mixed linear models with explicit maximum likelihood estimators (MLEs).Case-weighted perturbation schemes within and between subjects in mixed models are constructed. READ MORE
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8. On the Asymptotics of Increasing Dimension Models : Methods for Complete or Incomplete Data
Abstract : In some multivariate contexts there is a close relation between the number of parameters (p) and the number of observations (n). In a situation where p grows with n it frequently happens that the statistic does not converge to its true parameter. READ MORE
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9. Issues of incompleteness, outliers and asymptotics in high dimensional data
Abstract : This thesis consists of four individual essays and an introduction chapter. The essays are in the field of multivariate statistical analysis of High dimensional data. The first essay presents the issue of estimating the inverse covariance matrix alone and when it is used within the Mahalanobis distance in High-dimensional data. READ MORE
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10. Common features in vector nonlinear time series models
Abstract : This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in thesearea.Both stationary and nonstationary time series are concerned. READ MORE