Split-plot designs with general minimum lower-order confounding

查看全文 作　　者：WEI JiaLin 1,4,YANG JianFeng 1,LI Peng 3 & ZHANG RunChu 1,2,1 School of Mathematical Sciences and LPMC,Nankai University,Tianjin 300071,China;2 KLAS and School of Mathematics and Statistics,Northeast Normal University,Changchun 130024,China;3 School of Mathematical Sciences,Capital Normal University,Beijing 100037,China;4 School of Sciences,Tianjin University of Commerce,Tianjin 300134,China

出　　处：《Science China Mathematics》索引2010年第53卷第4期,共14页

基　　金：supported by National Natural Science Foundation of China (Grant No.10871104,10971107);the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No.20050055038) 摘　　要：Split-plot designs have been widely used in industrial experiments.Up to now,most methods for choosing this kind of designs are based on the minimum aberration (MA) criterion.Recently,by introducing a new pattern,called aliased effect-number pattern (AENP),Zhang et al.proposed a general minimum lowerorder confounding (denoted by GMC for short) criterion and established a general minimum confounding (also denoted by GMC for saving notations) theory.It is proved that,the GMC criterion selects optimal designs in a more elaborate manner than the existing ones,and when an experimenter has a prior about the importance ordering of factors in experiments the GMC designs are better than other optimal designs.In this paper we extend the GMC criterion to the split-plot design case and give a GMC-FFSP criterion for ranking split-plot designs.Some comparisons of the new criterion with the MA-MSA-FFSP criterion are given,and the optimal 32-run split-plot designs up to 14 factors under the two criteria are tabulated for comparison and application. 关键词：fractional FACTORIAL design GMC CRITERION minimum ABERRATION split-plot

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Split-plot designs with general minimum lower-order confounding

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