Robust designs for discriminating between trigonometric regression models

Abstract

The paper is devoted to the problem of constructing robust Т-optimal discriminating experimental designs for two competing trigonometric regression models, which differ by at most three trigonometric functions. To solve this problem we propose to use a Bayesian and standardized maximin approaches. In a number of special cases the robust T-optimal discriminating designs were found explicitly. In general case because of the complexity of the optimization problem, the corresponding optimal designs are not easy to find and have to be determined numerically. The results are illustrated in several examples.