Robust designs for the one-way random effects model using Q-estimators

dc.contributor.authorYang, Xiaolong
dc.contributor.supervisorZhou, Julie
dc.date.accessioned2009-12-04T20:28:36Z
dc.date.available2009-12-04T20:28:36Z
dc.date.copyright2006en
dc.date.issued2009-12-04T20:28:36Z
dc.degree.departmentDepartment of Mathematics and Statistics
dc.degree.levelMaster of Science M.Sc.en
dc.description.abstractRobust statistics is an extension of classical parametric statistics, which provides a safeguard against gross errors in experiments. Effectively, robustness properties of Uhlig's Q-estimators are examined and compared with that. of Rocke's Ai-estimators. In particular, the finite-sample implosion and explosion breakdown points are inves-tigated and introduced into constructing robust designs for the one-way random effects model. Optimal robust designs based on Uhlig's Q-estimation are similar to the ones based on Rocke's M-estimation. Ultimately. robust estimation procedures would provide steady and reliable estimates of model parameters in case of the occurrence of outliers.en
dc.identifier.urihttp://hdl.handle.net/1828/1945
dc.languageEnglisheng
dc.language.isoenen
dc.rightsAvailable to the World Wide Weben
dc.subjectrobust statisticsen
dc.subject.lcshUVic Subject Index::Sciences and Engineering::Mathematics::Mathematical statisticsen
dc.titleRobust designs for the one-way random effects model using Q-estimatorsen
dc.typeThesisen

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