Statistical modeling for experiments with sliding levels

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dc.creatorCheng, Shao-Wei
dc.creatorWu, C. F. J.
dc.creatorHuwang, Longcheen
dc.date2007-02-28
dc.date.accessioned2026-07-07T08:08:49Z
dc.date.available2026-07-07T08:08:49Z
dc.descriptionDesign of experiment with related factors can be implemented by using the technique of sliding levels. Taguchi (1987) proposed an analysis strategy by re-centering and re-scaling the slid factors. Hamada and Wu (1995) showed via counter examples that in many cases the interactions cannot be completely eliminated by Taguchi's strategy. They proposed an alternative method in which the slid factors are modeled by nested effects. In this work we show the inadequacy of both methods when the objective is response prediction. We propose an analysis method based on a response surface model, and demonstrate its superiority for prediction. We also study the relationships between these three modeling strategies.
dc.descriptionPublished at http://dx.doi.org/10.1214/074921706000001085 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0702862
dc.identifierhttp://arxiv.org/abs/math/0702862
dc.identifierIMS Lecture Notes Monograph Series 2006, Vol. 52, 245-256
dc.identifierdoi:10.1214/074921706000001085
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131392
dc.subjectStatistics Theory
dc.subject62K15, 62K20 (Primary) 62P30 (Secondary)
dc.titleStatistical modeling for experiments with sliding levels
dc.typetext

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