The Annals of Statistics

Bootstrap Procedures under some Non-I.I.D. Models

Regina Y. Liu

Full-text: Open access

Abstract

It is shown in this article that the classical i.i.d. bootstrap remains a valid procedure for estimating the sampling distributions of certain symmetric estimators of location, as long as the random observations are independently drawn from distributions with (essentially) a common location. This may be viewed as a robust property of the classical i.i.d. bootstrap. Also included is a study of the second order properties of a different bootstrap procedure proposed by Wu in the context of heteroscedasticity in regression.

Article information

Source
Ann. Statist., Volume 16, Number 4 (1988), 1696-1708.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176351062

Digital Object Identifier
doi:10.1214/aos/1176351062

Mathematical Reviews number (MathSciNet)
MR964947

Zentralblatt MATH identifier
0655.62031

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation

Keywords
Bootstrap non-i.i.d. models sampling distributions second order asymptotics regression $L$-statistics Edgeworth expansions

Citation

Liu, Regina Y. Bootstrap Procedures under some Non-I.I.D. Models. Ann. Statist. 16 (1988), no. 4, 1696--1708. doi:10.1214/aos/1176351062. https://projecteuclid.org/euclid.aos/1176351062


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