On the asymptotic behaviour of the integrated square error of kernel density estimators with data-dependent bandwidth

Carlos Tenreiro

Statistics & Probability Letters, 2001, vol. 53, issue 3, 283-292

Abstract: In this paper, we consider the integrated square error where f is the common density function of the independent and identically distributed random vectors X1,...,Xn and is the kernel estimator with a data-dependent bandwidth. Using the approach introduced by Hall (J. Multivariate Anal. 14 (1984) 1), and under some regularity conditions, we derive the L2 consistency in probability of and we establish an asymptotic expansion in probability and a central limit theorem for Jn.

Keywords: Kernel; estimators; Integrated; square; error; Asymptotic; distribution; U-statistics (search for similar items in EconPapers)
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(01)00072-4
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:53:y:2001:i:3:p:283-292

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().