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January, 1977 Robust Estimation in Dependent Situations
Stephen L. Portnoy
Ann. Statist. 5(1): 22-43 (January, 1977). DOI: 10.1214/aos/1176343738

Abstract

To analyze the effect of correlation in random samples on the performance of estimators of location, small correlation approximations for the asymptotic variance are found. Approximately optimal estimators (in the asymptotic minimax sense of Huber) are presented and compared to other estimators in terms of maximum asymptotic variance over the class of $\varepsilon$-contaminated normals. The presence of relatively small correlation can drastically inflate variances, and the optimal rules given here offer substantial improvements over previously considered estimators.

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Stephen L. Portnoy. "Robust Estimation in Dependent Situations." Ann. Statist. 5 (1) 22 - 43, January, 1977. https://doi.org/10.1214/aos/1176343738

Information

Published: January, 1977
First available in Project Euclid: 12 April 2007

zbMATH: 0355.62047
MathSciNet: MR445716
Digital Object Identifier: 10.1214/aos/1176343738

Subjects:
Primary: 62G35
Secondary: 62F10

Keywords: asymptotic minimaxity over $\epsilon$-contaminated normals , dependent observations , robust estimation

Rights: Copyright © 1977 Institute of Mathematical Statistics

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Vol.5 • No. 1 • January, 1977
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