Approximations for weighted bootstrap processes with an application

Lajos Horvath, Piotr Kokoszka and Josef Steinebach

Statistics & Probability Letters, 2000, vol. 48, issue 1, 59-70

Abstract: Let [beta]n(t) denote the weighted (smooth) bootstrap process of an empirical process. We show that the order of the best Gaussian approximation for [beta]n(t) is n-1/2 log n and we construct a sequence of approximating Brownian bridges achieving this rate. We also obtain an approximation for [beta]n(t) using a suitably chosen Kiefer process. The result is applied to detect a possible change in the distribution of independent observations.

Keywords: Weighted; bootstrap; Erdös-Rényi; law; Brownian; bridge; Best; approximation; Change-point; detection (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(99)00190-X
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:48:y:2000:i:1:p:59-70

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 ().