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dc.contributor.authorNoguchi, Kimihiro 19:19:44 (GMT) 19:19:44 (GMT)
dc.description.abstractThe problem of detecting monotonic increasing/decreasing trends in variances from k samples is widely met in many applications, e.g. financial data analysis, medical and environmental studies. However, most of the tests for equality of variances against ordered alternatives rely on the assumption of normality. Such tests are often non-robust to departures from normality, which eventually leads to unreliable conclusions. In this thesis, we propose a combination of a robust Levene-type test and a finite-intersection method, which relaxes the assumption of normality. The new combined procedure yields a more accurate estimate of sizes of the test and provides competitive powers. In addition, we discuss various modifications of the proposed test for unbalanced design cases. We present theoretical justifications of the new test and illustrate its applications by simulations and case studies.en
dc.publisherUniversity of Waterlooen
dc.subjectLevene's testen
dc.subjectEquality of variancesen
dc.subjectOrdered alternativesen
dc.subjectRobust testen
dc.titleCombination of Levene-Type Tests and a Finite-Intersection Method for Testing Trends in Variancesen
dc.typeMaster Thesisen
dc.subject.programStatisticsen and Actuarial Scienceen
uws-etd.degreeMaster of Mathematicsen

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