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Nonnormal Regression.I. Skew Distributions

dc.contributor.authorIslam, M. Qamarul
dc.contributor.authorL. Tiku, Moti
dc.contributor.authorYildirim, F.
dc.date.accessioned2024-04-25T07:16:51Z
dc.date.available2024-04-25T07:16:51Z
dc.date.issued2001
dc.departmentÇankaya Üniversitesi, İktisadi ve İdari Bilimler Fakültesi, İktisat Bölümüen_US
dc.description.abstractIn a linear regression model of the typey¼ Xþe, it is oftenassumed that the random erroreis normally distributed. Innumerous situations, e.g., whenymeasures life times or reac-tion times,etypically has a skew distribution. We considertwo important families of skew distributions, (a) Weibull withsupport IR:ð0,1Þon the real line, and (b) generalised logisticwit hsupport IR:ð 1,1Þ. Since the maximum likelihoodestimators are intractable in these situations, we derivemodified likelihood estimators which have explicit algebraicforms and are, therefore, easy to compute. We show that theseestimators are remarkably efficient, and robust. We develophypothesis testing procedures and give a real life exampleen_US
dc.identifier.citationIslam,M. Qamarul; L. Tiku,Moti; Yıldırım, F." Nonnormal Regression.I. Skew Distributions", Commun. Statist.—Theory Meth., Vol.30, No.6, pp.993-1020.en_US
dc.identifier.endpage1020en_US
dc.identifier.issue6en_US
dc.identifier.startpage993en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12416/7909
dc.identifier.volume30en_US
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectRobustnessen_US
dc.subjectMaximum Likelihooden_US
dc.subjectModifiedmaximum Likelihooden_US
dc.subjectLeast Squaresen_US
dc.subjectWeibullen_US
dc.subjectGeneralisedlogisticen_US
dc.titleNonnormal Regression.I. Skew Distributionstr_TR
dc.titleNonnormal Regression.i. Skew Distributionsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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