In real applications most experimental situations are influenced by a large number of different factors. In these settings the design of an experiment leads to challenging optimization problems, even if the underlying relationship can be described by a linear model. Based on recent research, this book introduces the theory of optimum designs for complex models and develops general methods of reduction to marginal problems for large classes of models with relevant interaction structures
CONTENT
I General Concepts -- 1 Foundations -- 2 A Review on Optimum Design Theory -- 3 Reduction Principles -- II Particular Classes of Multi-factor Models -- 4 Complete Product-Type Interactions -- 5 No Interactions -- 6 Partial Interactions -- 7 Some Additional Results -- Appendix on Partitioned Matrices -- References -- List of Symbols
