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March, 1978 An Efficient and Robust Adaptive Estimator of Location
Rudolf Beran
Ann. Statist. 6(2): 292-313 (March, 1978). DOI: 10.1214/aos/1176344125

Abstract

A nonparametric minimum Hellinger distance estimator of location is introduced and shown to be asymptotically efficient at every symmetric density with finite Fisher information. Under small, possibly asymmetric, perturbations in such a density, the estimator is asymptotically robust in a technical sense which extends Hajek's concept of "regularity." A numerical example illustrates the computational feasibility of the estimator and its resistance to an arbitrary single outlier.

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Rudolf Beran. "An Efficient and Robust Adaptive Estimator of Location." Ann. Statist. 6 (2) 292 - 313, March, 1978. https://doi.org/10.1214/aos/1176344125

Information

Published: March, 1978
First available in Project Euclid: 12 April 2007

zbMATH: 0378.62051
MathSciNet: MR518885
Digital Object Identifier: 10.1214/aos/1176344125

Subjects:
Primary: 62G05
Secondary: 62G35

Keywords: adaptive location estimator , asymptotically efficient , contiguity , minimum Hellinger distance , nonparametric estimator , robust estimator

Rights: Copyright © 1978 Institute of Mathematical Statistics

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Vol.6 • No. 2 • March, 1978
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