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December, 1989 Concavity and Estimation
Shelby J. Haberman
Ann. Statist. 17(4): 1631-1661 (December, 1989). DOI: 10.1214/aos/1176347385

Abstract

Simplified conditions are given for consistency and asymptotic normality of $M$-estimates derived by maximization of averages of independent identically distributed random concave functions. Applications are made to maximum likelihood estimation.

Citation

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Shelby J. Haberman. "Concavity and Estimation." Ann. Statist. 17 (4) 1631 - 1661, December, 1989. https://doi.org/10.1214/aos/1176347385

Information

Published: December, 1989
First available in Project Euclid: 12 April 2007

zbMATH: 0699.62027
MathSciNet: MR1026303
Digital Object Identifier: 10.1214/aos/1176347385

Subjects:
Primary: 62E20
Secondary: 62F10

Keywords: $M$-estimation , asymptotic normality , maximum likelihood , strong consistency

Rights: Copyright © 1989 Institute of Mathematical Statistics

Vol.17 • No. 4 • December, 1989
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