Improving bias in kernel density estimation

Kairat Mynbaev, Saralees Nadarajah, Christopher Withers and Aziza Aipenova

MPRA Paper from University Library of Munich, Germany

Abstract: For order $q$ kernel density estimators we show that the constant $b_q$ in $bias=b_qh^q+o(h^q)$ 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.

Keywords: Density estimation; bias; higher order kernel (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2014, Revised 2014
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Improving bias in kernel density estimation (2014)
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