Criterion-robust optimal designs for model discrimination and parameter estimation: Multivariate polynomial regression case

Min Hsiao Tsai, Mei-Mei Zen

研究成果: Article同行評審

16 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)591-601
頁數11
期刊Statistica Sinica
14
發行號2
出版狀態Published - 2004 四月

All Science Journal Classification (ASJC) codes

  • 數學(全部)
  • 統計與概率

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