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Matrix Image Method for Ranking Nonregular Fractional Factorial Designs 被引量:1

Matrix Image Method for Ranking Nonregular Fractional Factorial Designs
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摘要 Nonregular fractional factorial designs such as Plackett-Burman designs and other orthogonal arrays are widely used in various screening experiments for their run size economy and flexibility. In this paper,we study matrix image theory and present a new method for distinguishing and assessing nonregular designs with complex alias structure, which works for all symmetrical and asymmetrical, regular and nonregular orthogonal arrays. Based on the matrix image theory, our proposed method captures orthogonality and projection properties. Empirical studies show that the proposed method has a more precise differentiation capacity when comparing with some other criteria. Nonregular fractional factorial designs such as Plackett-Burman designs and other orthogonal arrays are widely used in various screening experiments for their run size economy and flexibility. In this paper,we study matrix image theory and present a new method for distinguishing and assessing nonregular designs with complex alias structure, which works for all symmetrical and asymmetrical, regular and nonregular orthogonal arrays. Based on the matrix image theory, our proposed method captures orthogonality and projection properties. Empirical studies show that the proposed method has a more precise differentiation capacity when comparing with some other criteria.
出处 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2018年第4期742-751,共10页 应用数学学报(英文版)
基金 supported by National Natural Science Foundation of China(Nos.11601195,11601538,11571073) Natural Science Foundation of Jiangsu Province of China(No.BK20160289) Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.16KJB110005) Jiangsu Qing Lan Project
关键词 generalized minimum aberration BAYES matrix image partial aliasing generalized minimum aberration Bayes matrix image partial aliasing
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