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.
Publié le : 2002-10-14
Classification:
Long- and short-range dependence,
kernel density estimators,
linear process,
martingale central limit theorem,
62F05,
60F17,
60G35
@article{1035844982,
author = {Wu, Wei Biao and Mielniczuk, Jan},
title = {Kernel density estimation for linear processes},
journal = {Ann. Statist.},
volume = {30},
number = {1},
year = {2002},
pages = { 1441-1459},
language = {en},
url = {http://dml.mathdoc.fr/item/1035844982}
}
Wu, Wei Biao; Mielniczuk, Jan. Kernel density estimation for linear processes. Ann. Statist., Tome 30 (2002) no. 1, pp. 1441-1459. http://gdmltest.u-ga.fr/item/1035844982/