On a weighted bootstrap approximation of the Lp norms of kernel density estimators

Bo Liu and Majid Mojirsheibani

Statistics & Probability Letters, 2015, vol. 105, issue C, 65-73

Abstract: A weighted bootstrap method is considered to approximate the distribution of the Lp norms of kernel density estimates. Here p is any number in [1,∞). Using a Komlós–Major–Tusnády type approximation (Komlós et al., 1975) for weighted bootstrap processes, due to Horváth et al. (2000), we establish unconditional bootstrap central limit theorems for these Lp statistics.

Keywords: Kernel; Density; CLT; Brownian bridge; Bootstrap (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715215001911
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:105:y:2015:i:c:p:65-73

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

DOI: 10.1016/j.spl.2015.06.005

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 ().