Construction Concepts for Continuum Regression

dc.contributor.authorSpitzner, Dan J.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2019-05-08T19:46:21Zen
dc.date.available2019-05-08T19:46:21Zen
dc.date.issued2004-08-28en
dc.description.abstractApproaches for meaningful regressor construction in the linear prediction problem are investigated in a framework similar to partial least squares and continuum regression, but weighted to allow for intelligent specification of an evaluative scheme. A cross-validatory continuum regression procedure is proposed, and shown to compare well with ordinary continuum regression in empirical demonstrations. Similar procedures are formulated from model-based constructive criteria, but are shown to be severely limited in their potential to enhance predictive performance. By paying careful attention to the interpretability of the proposed methods, the paper addresses a long-standing criticism that the current methodology relies on arbitrary mechanisms.en
dc.format.extent29 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.sourceurlhttps://www.stat.vt.edu/content/dam/stat_vt_edu/graphics-and-pdfs/research-papers/Technical_Reports/TechReport05-4.pdfen
dc.identifier.urihttp://hdl.handle.net/10919/89425en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.ispartofseriesTechnical Report No. 05-4en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectlinear predictionen
dc.subjectprincipal components regressionen
dc.subjectpartial least squares regressionen
dc.subjectcontinuum regressionen
dc.subjectweighted cross-validationen
dc.titleConstruction Concepts for Continuum Regressionen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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