Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1361
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dc.contributor.authorHuda, Shahariar
dc.contributor.authorMukerjee, Rahul
dc.date.accessioned2021-08-26T06:05:27Z-
dc.date.available2021-08-26T06:05:27Z-
dc.date.issued2013
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84883309910&doi=10.1016%2fj.jspi.2013.07.013&partnerID=40&md5=c279a2b1cbf12a6fe8626105ed4d3c2c
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/1361-
dc.descriptionHuda, Shahariar, Department of Statistics, Faculty of Science, Kuwait University, P.O. Box-5969, Safat-13060, Kuwait; Mukerjee, Rahul, Indian Institute of Management Calcutta, Kolkata 700 104, India
dc.descriptionISSN/ISBN - 03783758
dc.descriptionpp.1872-1879
dc.descriptionDOI - 10.1016/j.jspi.2013.07.013
dc.description.abstractFor two-level factorials, we consider designs in N=2 (mod 4) runs as obtained by adding two runs, with a certain coincidence pattern, to an orthogonal array of strength two. These designs are known to be optimal main effect plans in a very broad sense in the absence of interactions. Among them, we explore the ones having minimum aberration, with a view to ensuring maximum model robustness even when interactions are possibly present. This is done by sequentially minimizing a measure of the bias caused by interactions of successively higher orders. � 2013 Elsevier B.V.
dc.publisherSCOPUS
dc.publisherJournal of Statistical Planning and Inference
dc.relation.ispartofseries143(11)
dc.subjectBias
dc.subjectEffect hierarchy
dc.subjectHadamard matrix
dc.subjectNonorthogonality
dc.subjectOrthogonal array
dc.titleTwo-level minimum aberration designs in N =2 (mod 4) runs
dc.typeArticle
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