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)