Kernel quantile estimtion for heavy-tailed distributions

Please use this identifier to cite or link to this item: http://archives.univ-biskra.dz/handle/123456789/4675

Full metadata record

DC Field	Value	Language
dc.contributor.author	Sayah, Abdallah	-
dc.date.accessioned	2014-12-03T13:34:34Z	-
dc.date.available	2014-12-03T13:34:34Z	-
dc.date.issued	2014-12-03	-
dc.identifier.uri	http://archives.univ-biskra.dz/handle/123456789/4675	-
dc.description.abstract	By transforming a data set with a modiÖcation 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.	en_US
dc.language.iso	en	en_US
dc.relation.ispartofseries	Mathématique;	-
dc.subject	Bandwidth	en_US
dc.subject	Champernowne distribution	en_US
dc.subject	Heavy tails	en_US
dc.subject	Kernel estimator	en_US
dc.subject	Quantile function	en_US
dc.title	Kernel quantile estimtion for heavy-tailed distributions	en_US
dc.type	Thesis	en_US
Appears in Collections:	Faculté des Sciences Exactes et des Science de la Nature et de la vie (FSESNV)

Files in This Item:

File	Description	Size	Format
Kernel quantile estimtion for heavy-tailed distributions.pdf		451,55 kB	Adobe PDF	View/Open