Please use this identifier to cite or link to this item: http://archives.univ-biskra.dz/handle/123456789/2262
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dc.contributor.authorAbdallah Sayah-
dc.contributor.authorDjabrane Yahia-
dc.contributor.author, Abdelhakim Necir-
dc.date.accessioned2013-04-11T13:20:01Z-
dc.date.available2013-04-11T13:20:01Z-
dc.date.issued2013-04-11-
dc.identifier.urihttp://archives.univ-biskra.dz/handle/123456789/2262-
dc.description.abstractBy transforming a data set with a modification of the Champernowne distribution function, a kernel quantile estimator for heavy-tailed distributions is given. The asymptotic mean squared error (AMSE) of the proposed estimator and related asymptotically optimal bandwidth are evaluated. Some simulations are drawn to show the performance of the obtained results.Link http://www.ajol.info/index.php/afst/article/view/71075en_US
dc.subjectBandwidthen_US
dc.subjectChampernowne distributionen_US
dc.subjectHeavy tailsen_US
dc.subjectKernel estimatoren_US
dc.subjectQuantile functionen_US
dc.titleChampernowne transformation in kernel quantile estimation for heavy-tailed distributionsen_US
dc.typeArticleen_US
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