Open Access
Translator Disclaimer
October 2002 Kernel density estimation for linear processes
Wei Biao Wu, Jan Mielniczuk
Ann. Statist. 30(5): 1441-1459 (October 2002). DOI: 10.1214/aos/1035844982

Abstract

In this paper we provide a detailed characterization of the asymptotic behavior of kernel density estimators for one-sided linear processes. The conjecture that asymptotic normality for the kernel density estimator holds under short-range dependence is proved under minimal assumptions on bandwidths. We also depict the dichotomous and trichotomous phenomena for various choices of bandwidths when the process is long-range dependent.

Citation

Download Citation

Wei Biao Wu. Jan Mielniczuk. "Kernel density estimation for linear processes." Ann. Statist. 30 (5) 1441 - 1459, October 2002. https://doi.org/10.1214/aos/1035844982

Information

Published: October 2002
First available in Project Euclid: 28 October 2002

zbMATH: 1015.62034
MathSciNet: MR1936325
Digital Object Identifier: 10.1214/aos/1035844982

Subjects:
Primary: 60F17 , 62F05
Secondary: 60G35

Keywords: kernel density estimators , linear process , Long- and short-range dependence , martingale central limit theorem

Rights: Copyright © 2002 Institute of Mathematical Statistics

JOURNAL ARTICLE
19 PAGES


SHARE
Vol.30 • No. 5 • October 2002
Back to Top