Optimal Experimental Design

Course plan

The course is about optimal experimental design – planning of experiments. The basic idea of design optimization (best estimation of unknown model parameters, information or moment matrix, etc.) and commonly used design criteria in linear models are the main parts of the course. Besides optimal designs in classical linear models, optimal designs for estimation and prediction of fixed and random effects in particular mixed models will be discussed.

Contents (tentative)
1. Introduction
2. Optimal Design in Fixed Effects Models
2.1. Best linear unbiased estimator
2.2. Information Matrix
2.3. Design Criteria
2.4. Examples
3. Optimal Design in Random Coefficients Regression Models
3.1. Models with Known Population Parameters
3.1.1. Best Estimation
3.1.2. Design Criteria
3.1.3. Examples
3.2. Models with Unknown Population Parameters
3.2.1. BLUE and BLUP
3.2.2. Information Matrices
3.2.3. Design Criteria
3.2.4. Examples
4. Discussion on Optimal Designs in More Complex Models

3 credits

Schedule: The course is given in the second period of the spring in distance mode (more details will be available shortly).

Lecturer: Maryna Prus

Contact lecturer on maryna.prus@liu.se or fredrik.lindsten@liu.se for more information/registration.

Graduate course (liu.se)

Course Data
Type of schedule: 
Travel friendly schedule
Credits (ECTS):