实验设计
计算机科学
曲率
订单(交换)
数学
二次方程
过程(计算)
班级(哲学)
极限(数学)
数学优化
统计
人工智能
财务
经济
数学分析
几何学
操作系统
作者
Bradley Jones,Christopher J. Nachtsheim
标识
DOI:10.1080/00224065.2011.11917841
摘要
Screening designs are attractive for assessing the relative impact of a large number of factors on a response of interest. Experimenters often prefer quantitative factors with three levels over two-level factors because having three levels allows for some assessment of curvature in the factor—response relationship. Yet, the most familiar screening designs limit each factor to only two levels. We propose a new class of designs that have three levels, provide estimates of main effects that are unbiased by any second-order effect, require only one more than twice as many runs as there are factors, and avoid confounding of any pair of second-order effects. Moreover, for designs having six factors or more, our designs allow for the efficient estimation of the full quadratic model in any three factors. In this respect, our designs may render follow-up experiments unnecessary in many situations, thereby increasing the efficiency of the entire experimentation process. We also provide an algorithm for design construction.
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