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Nonnormal Regression.I. Skew Distributions

dc.contributor.author Islam, M. Qamarul
dc.contributor.author L. Tiku, Moti
dc.contributor.author Yildirim, F.
dc.date.accessioned 2024-04-25T07:16:51Z
dc.date.available 2024-04-25T07:16:51Z
dc.date.issued 2001
dc.department Çankaya Üniversitesi, İktisadi ve İdari Bilimler Fakültesi, İktisat Bölümü en_US
dc.description.abstract In 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 example en_US
dc.identifier.citation Islam,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.endpage 1020 en_US
dc.identifier.issue 6 en_US
dc.identifier.startpage 993 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12416/7909
dc.identifier.volume 30 en_US
dc.language.iso en en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Robustness en_US
dc.subject Maximum Likelihood en_US
dc.subject Modifiedmaximum Likelihood en_US
dc.subject Least Squares en_US
dc.subject Weibull en_US
dc.subject Generalisedlogistic en_US
dc.title Nonnormal Regression.I. Skew Distributions tr_TR
dc.title Nonnormal Regression.i. Skew Distributions en_US
dc.type Article en_US
dspace.entity.type Publication

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