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dc.contributor.authorMukerjee, Rahul
dc.contributor.authorTang, Boxin
dc.descriptionMukerjee, Rahul, Indian Institute of Management Calcutta, Joka, Diamond Harbour Road, Kolkata, 700 104, India; Tang, Boxin, Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
dc.descriptionISSN/ISBN - 10170405
dc.descriptionDOI - 10.5705/ss.202015.0214
dc.description.abstractWe consider two-level fractional factorial designs under a baseline parametrization that arises naturally when each factor has a control or baseline level. While the criterion of minimum aberration can be formulated as usual on the basis of the bias that interactions can cause in the estimation of main effects, its study is hindered by the fact that level permutation of any factor can impact such bias. This poses a serious challenge especially in the practically important highly fractionated situations where the number of factors is large. We address this problem for regular designs via explicit consideration of the principal fraction and its cosets, and obtain certain rank conditions which, in conjunction with the idea of minimum moment aberration, are seen to work well. The role of simple recursive sets is also examined with a view to achieving further simplification. Details on highly fractionated minimum aberration designs having up to 256 runs are provided.
dc.publisherStatistica Sinica
dc.publisherInstitute of Statistical Science
dc.subjectLevel permutation
dc.subjectMinimum aberration
dc.subjectOrthogonal array
dc.subjectPrincipal fraction
dc.subjectRank condition
dc.subjectSimple recursive set
dc.titleOptimal two-level regular designs under baseline parametrization via cosets and minimum moment aberration
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