Analysis on $$s^{n-m}$$ s n - m designs with general minimum lower-order confounding

Zhiming Li (), Zhidong Teng (), Tianfang Zhang () and Runchu Zhang ()
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Zhiming Li: Xinjiang University
Zhidong Teng: Xinjiang University
Tianfang Zhang: Jiangxi Normal University
Runchu Zhang: Northeast Normal University

AStA Advances in Statistical Analysis, 2016, vol. 100, issue 2, No 4, 207-222

Abstract: Abstract An optimal design should minimize the confounding among factor effects, especially the lower-order effects, such as main effects and two-factor interaction effects. Based on the aliased component-number pattern, general minimum lower-order confounding (GMC) criterion can provide the confounding information among factors of designs in a more elaborate and explicit manner. In this paper, we extend GMC theory to s-level regular designs, where s is a prime or prime power. For an $$s^{n-m}$$ s n - m design D with $$N=s^{n-m}$$ N = s n - m runs, the confounding of design D is given by complementary set. Further, according to the factor number n, we discuss two cases: (i) $$N/s

Keywords: s-level design; Component effect hierarchy principle; Aliased component-number pattern; General minimum lower-order confounding; GMC design; Complementary set; Primary 62K05; Secondary 62K15 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10182-015-0259-3

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