Please use this identifier to cite or link to this item:
http://archives.univ-biskra.dz/handle/123456789/2262| Title: | Champernowne transformation in kernel quantile estimation for heavy-tailed distributions |
| Authors: | Abdallah Sayah Djabrane Yahia , Abdelhakim Necir |
| Keywords: | Bandwidth Champernowne distribution Heavy tails Kernel estimator Quantile function |
| Issue Date: | 11-Apr-2013 |
| Abstract: | By 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/71075 |
| URI: | http://archives.univ-biskra.dz/handle/123456789/2262 |
| Appears in Collections: | Publications Internationales |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Bias-reduced estimation of Wang's two-sided deviation risk measure under Levy-stable regime.pdf | 35,63 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.