The Annals of Statistics

A Linearized Version of the Hodges-Lehmann Estimator

Andre Antille

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Abstract

In the estimation of a location parameter the Hodges-Lehmann estimator is known to have some "robust" properties, but it is very "expensive" for large sample sizes. By using the linearity of a special rank statistic we can find a linearized version which requires only $O(n \log n)$ operations.

Article information

Source
Ann. Statist., Volume 2, Number 6 (1974), 1308-1313.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176342883

Digital Object Identifier
doi:10.1214/aos/1176342883

Mathematical Reviews number (MathSciNet)
MR365868

Zentralblatt MATH identifier
0296.62035

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation
Secondary: 62G25 62E15: Exact distribution theory 60F05: Central limit and other weak theorems

Keywords
One-sample problem linear rank statistic asymptotic variance weak convergence of stochastic processes

Citation

Antille, Andre. A Linearized Version of the Hodges-Lehmann Estimator. Ann. Statist. 2 (1974), no. 6, 1308--1313. doi:10.1214/aos/1176342883. https://projecteuclid.org/euclid.aos/1176342883


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