Consider the problem of discriminating between two polynomial regression models on the q-cube [-1, 1] q, q ≥ 2, and estimating parameters in the models. To find designs which are efficient for both model discrimination and parameter estimation, Zen and Tsai (2002) proposed a multiple-objective optimality criterion for the univariate case. In this work, taking the same M γ-criterion which uses weight γ (0 ≤ γ ≤ 1) for model discrimination and 1 - γ for parameter estimation, the corresponding M γ-optimal product design is investigated. Based on the maximin principle on the M γ-efficiency of any M γ′-optimal product design, a criterion-robust optimal product design is proposed.
|Number of pages||11|
|Publication status||Published - 2004 Apr|
All Science Journal Classification (ASJC) codes
- Statistics and Probability