A Combinatorial Search Technique for Constructing Optimal Designs for Biased Models

摘要

A new algorithm has been proposed to locate the global minimum of the alias matrix for a biased response function defined in a set of distinct support points. The search begins by classifying all the support points in the experimental region of interest into groups. Then starting from an arbitrary set of N support points, the algorithm obtains an N-point optimal design by systematically adding and dropping support points from the various groups in such a way as to continuously reduce the determinant of the alias matrix of the design at each step of the sequence. Numerical demonstrations confirm the effectiveness of this algorithm.