Sökning: "dietrich von rosen"
Visar resultat 1 - 5 av 24 avhandlingar innehållade orden dietrich von rosen.
1. Explicit Influence Analysis in Crossover Models
Sammanfattning : 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. LÄS MER
2. Local Influence Analysis and Cross-over Studies
Sammanfattning : 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. LÄS MER
3. A study of multilevel models with block circular symmetric covariance structures
Sammanfattning : 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. LÄS MER
4. Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
Sammanfattning : 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. LÄS MER
5. Multivariate linear normal models with special references to the growth curve model
Sammanfattning : The Growth Curve Model (GMAN0VA) introduced by Potthoff & Roy (1964) and two extensions are considered. The first extension treats a Growth Curve Model with concomitant variables whereas the second is applicable when different growth curves or when linear restrictions on the parameter space, describing the mean structure in the Growth Curve Model, exist. LÄS MER