A general criterion for factorial designs under model uncertainty

Pi Wen Tsai*, Steven G. Gilmour

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

12 引文 斯高帕斯(Scopus)

摘要

Motivated by two industrial experiments in which rather extreme prior knowledge was used to choose the design, we show that the QB criterion, which aims to improve the estimation in as many models as possible by incorporating experimenters' prior knowledge along with an approximation to the As criterion, is more general and has a better statistical interpretation than many standard criteria. The generalization and application of the criterion to different types of designs are presented. The relationships between QB and other criteria for different situations are explored. It is shown that the E(s2) criterion is a special case of QB and several aberration-type criteria are limiting cases of our criterion, so that QB provides a bridge between alphabetic optimality and aberration. The two case studies illustrate the potential benefits of the QB criterion. R programs for calculating QB are available online as supplemental materials.

原文英語
頁(從 - 到)231-242
頁數12
期刊Technometrics
52
發行號2
DOIs
出版狀態已發佈 - 2010 五月

ASJC Scopus subject areas

  • 統計與概率
  • 建模與模擬
  • 應用數學

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