Semiparametric Techniques for Response Surface Methodology

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dc.contributor.authorPickle, Stephanie M.en
dc.contributor.committeechairBirch, Jeffrey B.en
dc.contributor.committeecochairRobinson, Timothy J.en
dc.contributor.committeememberSpitzner, Dan J.en
dc.contributor.committeememberPrins, Samantha C. Batesen
dc.contributor.committeememberVining, G. Geoffreyen
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T20:14:43Zen
dc.date.adate2006-09-14en
dc.date.available2014-03-14T20:14:43Zen
dc.date.issued2006-06-28en
dc.date.rdate2009-09-14en
dc.date.sdate2006-08-04en
dc.description.abstractMany industrial statisticians employ the techniques of Response Surface Methodology (RSM) to study and optimize products and processes. A second-order Taylor series approximation is commonly utilized to model the data; however, parametric models are not always adequate. In these situations, any degree of model misspecification may result in serious bias of the estimated response. Nonparametric methods have been suggested as an alternative as they can capture structure in the data that a misspecified parametric model cannot. Yet nonparametric fits may be highly variable especially in small sample settings which are common in RSM. Therefore, semiparametric regression techniques are proposed for use in the RSM setting. These methods will be applied to an elementary RSM problem as well as the robust parameter design problem.en
dc.description.degreePh. D.en
dc.identifier.otheretd-08042006-075722en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08042006-075722/en
dc.identifier.urihttp://hdl.handle.net/10919/28517en
dc.publisherVirginia Techen
dc.relation.haspartSMPickle_Dissertation.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectGenetic Algorithmen
dc.subjectResponse Surface Methodologyen
dc.subjectSemiparametric Regressionen
dc.subjectRobust Parameter Designen
dc.titleSemiparametric Techniques for Response Surface Methodologyen
dc.typeDissertationen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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