Search for dissertations about: "Tatjana Von Rosen"
Showing result 1 - 5 of 9 swedish dissertations containing the words Tatjana Von Rosen.
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1. Explicit Influence Analysis in Crossover Models
Abstract : This dissertation develops influence diagnostics for crossover models. Mixed linear models and generalised mixed linear models are utilised to investigate continuous and count data from crossover studies, respectively. READ MORE
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2. 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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3. A study of multilevel models with block circular symmetric covariance structures
Abstract : This thesis concerns the study of multilevel models with specific patterned covariance structures and addresses the issues of maximum likelihoodestimation. In particular, circular symmetric hierarchical datastructures are considered. READ MORE
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4. 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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5. Modeling Realized Covariance of Asset Returns
Abstract : In this thesis, which consists of two papers, we consider the modeling of positive definitive symmetric matrices, in particular covariance matrices of financial asset returns. The return covariance matrix describes the magnitude in which prices of financial assets tend to change over time, and how price changes between different assets are related. READ MORE