Minimax robust designs for misspecified regression models

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dc.contributor.author Shi, Peilin
dc.date.accessioned 2018-11-10T01:07:35Z
dc.date.available 2018-11-10T01:07:35Z
dc.date.copyright 2002 en_US
dc.date.issued 2018-11-09
dc.identifier.uri https://dspace.library.uvic.ca//handle/1828/10291
dc.description.abstract Minimax robust designs are studied for regression models with possible misspecified response functions. These designs, minimizing the maximum of the mean squared error matrix, can control the bias caused by model misspecification and the desired efficiency through one parameter. Using nonsmooth optimization technique, we derive the minimax designs analytically for misspecified regression models. This extends the results in Heo, Schmuland and Wiens (2001). Several examples are discussed for approximately polynomial regression. en_US
dc.language English eng
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.subject Traffic flow en_US
dc.subject Mathematical models en_US
dc.subject Regression en_US
dc.subject Misspecified regression en_US
dc.title Minimax robust designs for misspecified regression models en_US
dc.type Thesis en_US
dc.contributor.supervisor Ye, Jane J.
dc.contributor.supervisor Zhou, Julie
dc.degree.department Department of Mathematics and Statistics en_US
dc.degree.level Doctor of Philosophy Ph.D. en_US
dc.description.scholarlevel Graduate en_US

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