Afrika Statistika

Champernowne transformation in kernel quantile estimation for heavy-tailed distributions

Abdalla Sayah, Djabrane Yahia, and Abdelhakim Necir

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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

Article information

Source
Afr. Stat., Volume 5, Number 1 (2010), 288-296.

Dates
First available in Project Euclid: 1 January 2014

Permanent link to this document
https://projecteuclid.org/euclid.as/1388545351

Mathematical Reviews number (MathSciNet)
MR2920306

Zentralblatt MATH identifier
1327.62225

Subjects
Primary: 62G05: Estimation 62G32: Statistics of extreme values; tail inference

Keywords
Bandwidth Champernowne distribution Heavy tails Kernel estimator Quantile function

Citation

Sayah, Abdalla; Yahia, Djabrane; Necir, Abdelhakim. Champernowne transformation in kernel quantile estimation for heavy-tailed distributions. Afr. Stat. 5 (2010), no. 1, 288--296. https://projecteuclid.org/euclid.as/1388545351


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