Projections of Definitive Screening Designs by Dropping Columns: Selection and Evaluation 期刊名称： Technometrics
作者： Alan R. Vazquez,Peter Goos,Eric D. Schoen
年份： 2019年
期号： 第1期
关键词： Conference matrix;D-efficiency;Isomorphism;Second-order model;Two-factor interaction
brooke fraser摘要：Definitive screening designs permit the study of many quantitative factors on a response in a few runs more than twice the number of factors. In practical applications, researchers often require a design for m quantitative factors, construct a definitive screening design for more than m factors and drop the superfluous columns. This is done when the number of runs in the standard m-factor definitive screening design is considered too limited or when no standard definitive screening design exists for m factors. In these cases, it is common practice to arbitrarily drop the last columns of the larger design. In this article,
we show that certain statistical properties of the resulting experimental design depend on the exact columns to be dropped and that other properties are insensitive to these columns. We perform a complete search