Open Access
June, 1991 Minimaxity of the Empirical Distribution Function in Invariant Estimation
Qiqing Yu, Mo-suk Chow
Ann. Statist. 19(2): 935-951 (June, 1991). DOI: 10.1214/aos/1176348129

Abstract

Consider the problem of continuous invariant estimation of a distribution function with the weighted Cramer-von Mises loss. The minimaxity of the empirical distribution function, which is also the best invariant estimator, is proved for any sample size. This solves a long-standing conjecture.

Citation

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Qiqing Yu. Mo-suk Chow. "Minimaxity of the Empirical Distribution Function in Invariant Estimation." Ann. Statist. 19 (2) 935 - 951, June, 1991. https://doi.org/10.1214/aos/1176348129

Information

Published: June, 1991
First available in Project Euclid: 12 April 2007

zbMATH: 0739.62011
MathSciNet: MR1105853
Digital Object Identifier: 10.1214/aos/1176348129

Subjects:
Primary: 62C15
Secondary: 62D05

Keywords: Baire category theorem , Cramer-von Mises loss , Egoroff's theorem , invariant estimator , Minimaxity within a class , nonparametric estimator , Product measure

Rights: Copyright © 1991 Institute of Mathematical Statistics

Vol.19 • No. 2 • June, 1991
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