Cost Penalized Estimation and Prediction Evaluation for Split-Plot Designs

dc.contributor.authorLiang, Lien
dc.contributor.authorAnderson-Cook, Christine M.en
dc.contributor.authorRobinson, Timothy J.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2019-05-08T19:46:19Zen
dc.date.available2019-05-08T19:46:19Zen
dc.date.issued2005-02-02en
dc.description.abstractThe use of response surface methods generally begins with a process or system involving a response y that depends on a set of k controllable input variables (factors) x₁, x₂,…,xk. To assess the effects of these factors on the response, an experiment is conducted in which the levels of the factors are varied and changes in the response are noted. The size of the experimental design (number of distinct level combinations of the factors as well as number of runs) depends on the complexity of the model the user wishes to fit. Limited resources due to time and/or cost constraints are inherent to most experiments, and hence, the user typically approaches experimentation with a desire to minimize the number of experimental trials while still being able to adequately estimate the underlying model.en
dc.format.extent33 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.sourceurlhttps://www.stat.vt.edu/content/dam/stat_vt_edu/graphics-and-pdfs/research-papers/Technical_Reports/TechReport05-1.pdfen
dc.identifier.urihttp://hdl.handle.net/10919/89414en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.ispartofseriesTechnical Report No. 05-1en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleCost Penalized Estimation and Prediction Evaluation for Split-Plot Designsen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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