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
Citation
Abdalla Sayah. Djabrane Yahia. Abdelhakim Necir. "Champernowne transformation in kernel quantile estimation for heavy-tailed distributions." Afr. Stat. 5 (1) 288 - 296, April 2010.
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