universiteit antwerpen - Peter Goos - Optimal Design course

Introductory course on

The Optimal Design of Experiments

(contents: see below)

December 5, 6 & 7, 2012

Antwerp, Belgium

The target audience for the course is starting Ph.D. students and anyone else who would like a primer on optimal design. Prerequisites for the course are knowledge of basic statistics and regression analysis. Familiarity with classical design of experiments is not required. The course is not highly mathematical and therefore accessible to a broad audience.

The course will start with an intuitive introduction of the topic and gradually builds up to more complicated situations. Examples for the course will be taken from industry, marketing, chemistry, medicine, ... to show the wide applicability of the optimal design techniques. The attention will not be restricted to optimal design for linear regression models, but Bayesian optimal design and minimax designs for nonlinear regression models will also be discussed. The strengths and weaknesses of optimal design will be illustrated, and some remedies to overcome some of the problems will be given.

The venue for the course is in the Antwerp city center, Prinsstraat 10, room P201. Registration for the course costs 150 euro for academics and 750 euro for others. This fee includes course material and lunches on December 6 and 7. Registrants can arrange cheap accomodation in nearby hotels. The Antwerp city center is easy to reach by train, and there is an hourly bus service from and to Brussels National Airport.

For further information, please contact Peter Goos at mailto:peter.goos@ua.ac.be

Course contents:

In total, the course takes 2.5 days. The programme of the first 2 days is as follows:

- Introduction to design of experiments

- Intuitive introduction to optimal design of experiments

- Optimal design for linear regression models ( first-order models, second-order models, constrained design regions, algorithms)

- Optimal design for nonlinear regression models ( local optimal design, Bayesian optimal design, minimax design, algorithms)

- Extensions to non-standard design problems ( blocked experiments, paired comparison and choice experiments, experiments with hard-to-change factors (split-plot experiments), model uncertainty)

The last half day is reserved for advanced topics like split-split-plot designs, strip-plot designs, and computationally efficient methods for Bayesian optimal design.

The course will take place in a computer class so that the course participants can work on a few algorithms and examples themselves. Various software packages are demonstrated as well.

Schedule: 5 December (1.30pm-5.30pm), 6 & 7 December (9am-5.30pm)