Methods of calibration for the empirical likelihood ratio

dc.contributor.authorJiang, Li
dc.contributor.supervisorTsao, M.
dc.date.accessioned2009-11-17T19:19:35Z
dc.date.available2009-11-17T19:19:35Z
dc.date.copyright2006en
dc.date.issued2006
dc.degree.departmentDepartment of Mathematics and Statistics
dc.degree.levelMaster of Applied Science M.A.Sc.en
dc.description.abstractThis thesis provides several new calibration methods for the empirical log-likelihood ratio. The commonly used Chi-square calibration is based on the limiting distribu¬tion of this ratio but it constantly suffers from the undercoverage problem. The finite sample distribution of the empirical log-likelihood ratio is recognized to have a mix¬ture structure with a continuous component on [0, +∞) and a probability mass at +∞. Consequently, new calibration methods are developed to take advantage of this mixture structure; we propose new calibration methods based on the mixture distrib¬utions, such as the mixture Chi-square and the mixture Fisher's F distribution. The E distribution introduced in Tsao (2004a) has a natural mixture structure and the calibration method based on this distribution is considered in great details. We also discuss methods of estimating the E distributions.en
dc.identifier.urihttp://hdl.handle.net/1828/1854
dc.languageEnglisheng
dc.language.isoenen
dc.rightsAvailable to the World Wide Weben
dc.subjectcalibrationen
dc.subjectChi-squareen
dc.subjecteimpiricalen
dc.subject.lcshUVic Subject Index::Sciences and Engineering::Mathematics::Mathematical statisticsen
dc.titleMethods of calibration for the empirical likelihood ratioen
dc.typeThesisen

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