Formulas for the exact LMS and LQS estimators

dc.authoridhttps://orcid.org/0000-0001-6123-2508en_US
dc.contributor.authorKiracı, Arzdar
dc.date.accessioned2020-06-25T08:36:38Z
dc.date.available2020-06-25T08:36:38Z
dc.date.issued2011en_US
dc.departmentİktisadi İdari Bilimler Fakültesien_US
dc.description.abstractThe author presents the derivation of formulas for the calculation of critical values of the median function or the general version of it, namely, the quantile functions. In statistics, these functions are used to detect outliers in the data set and to make predictions that are resistant to outliers. Therefore, these formulas can also be used as estimators for these regressions. The fact that these formulas are able to calculate the global optimum gives the exact least median squares or the exact least quantile of squares estimators. The author provides the theoretical background for deriving these estimator formulas and derives the estimator formulas for regression models up to three parameters. In addition, the author provides guides for the derivation of formulas for other models, illustrates the use of these formulas, and emphasizes their properties that are useful for future works. One important conclusion is that each regression model has its own set of formulas.en_US
dc.identifier.endpage543en_US
dc.identifier.issue3en_US
dc.identifier.startpage530en_US
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/03610926.2010.529523
dc.identifier.urihttps://hdl.handle.net/20.500.12604/2713
dc.identifier.volume41en_US
dc.institutionauthorKiracı, Arzdar
dc.language.isoenen_US
dc.publisherCommunications in Statistics - Theory and Methodsen_US
dc.relation.publicationcategoryMakale - Uluslararası - Editör Denetimli Dergien_US
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_US
dc.snmz#KayıtKontrol#
dc.subjectExact estimatorsen_US
dc.titleFormulas for the exact LMS and LQS estimatorsen_US
dc.typeArticleen_US

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