Sökning: "D-optimality"
Visar resultat 1 - 5 av 8 avhandlingar innehållade ordet D-optimality.
1. Effective Sampling Design for Groundwater Transport Models
Sammanfattning : Model reliability is important when groundwater models are used for evaluation of environmental impact and water resource management. Model attributes such as geohydrologic units and parameter values need to be quantified in order to obtain reliable results. LÄS MER
2. Optimal Design and Inference for Correlated Bernoulli Variables using a Simplified Cox Model
Sammanfattning : This thesis proposes a simplification of the model for dependent Bernoulli variables presented in Cox and Snell (1989). The simplified model, referred to as the simplified Cox model, is developed for identically distributed and dependent Bernoulli variables. LÄS MER
3. Optimal Design of Experiments for the Quadratic Logistic Model
Sammanfattning : Optimal design of experiments for binary data is the topic of this thesis. A particular logistic model including a quadratic term in the linear predictor is considered. Determining an optimal design for this model is complicated by the fact that the optimal design is dependent on the unknown true parameters. LÄS MER
4. Simulation based design : structural optimization at early design stages
Sammanfattning : The aim of this thesis is to evaluate and develop different modelling tools which can be used in the vehicle crashworthiness design process. These tools will improve the understanding of the vehicle behaviour and thus improve the crashworthiness of the vehicle. LÄS MER
5. Benefits of Non-Linear Mixed Effect Modeling and Optimal Design : Pre-Clinical and Clinical Study Applications
Sammanfattning : Despite the growing promise of pharmaceutical research, inferior experimentation or interpretation of data can inhibit breakthrough molecules from finding their way out of research institutions and reaching patients. This thesis provides evidence that better characterization of pre-clinical and clinical data can be accomplished using non-linear mixed effect modeling (NLMEM) and more effective experiments can be conducted using optimal design (OD). LÄS MER