Improving bias in kernel density estimation

For order q kernel density estimators we show that the constant bq in bias=bqhq+o(hq) can be made arbitrarily small, while keeping the variance bounded. A data-based selection of bq is presented and Monte Carlo simulations illustrate the advantages of the method.

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Year of publication:	2014
Authors:	Mynbaev, Kairat T. ; Nadarajah, Saralees ; Withers, Christopher S. ; Aipenova, Aziza S.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 94.2014, C, p. 106-112
Publisher:	Elsevier
Subject:	Density estimation \| Bias \| Higher order kernel

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010930588