A Generalized General Minimum Lower Order Confounding Criterion for General Orthogonal Designs

Yi Cheng and Runchu Zhang

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 14, 4799-4814

Abstract: In this article, we extend the AENP and the GMC criterion proposed by Zhang et al. (2008) to the case of nonregular orthogonal designs. A G-AENP and correspondingly a G-GMC criterion are proposed. The confounding frequency vector (CFV) and the generalized wordlength pattern (GWLP), as the base of MGA and GMA criteria, are shown to be functions of the G-AENP. Some optimal properties of G-GMC designs are obtained. At the last, we give an efficient algorithm for finding optimal designs and tabulate some G-GMC designs with 16- and 18-run for application and comparison with GMA and MGA designs.

Date: 2023
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DOI: 10.1080/03610926.2013.765474

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