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December, 1988 Asymptotic Behavior of Statistical Estimators and of Optimal Solutions of Stochastic Optimization Problems
Jitka Dupacova, Roger Wets
Ann. Statist. 16(4): 1517-1549 (December, 1988). DOI: 10.1214/aos/1176351052

Abstract

We study the asymptotic behavior of the statistical estimators that maximize a not necessarily differentiable criterion function, possibly subject to side constraints (equalities and inequalities). The consistency results generalize those of Wald and Huber. Conditions are also given under which one is still able to obtain asymptotic normality. The analysis brings to the fore the relationship between the problem of finding statistical estimators and that of finding the optimal solutions of stochastic optimization problems with partial information. The last section is devoted to the properties of the saddle points of the associated Lagrangians.

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Jitka Dupacova. Roger Wets. "Asymptotic Behavior of Statistical Estimators and of Optimal Solutions of Stochastic Optimization Problems." Ann. Statist. 16 (4) 1517 - 1549, December, 1988. https://doi.org/10.1214/aos/1176351052

Information

Published: December, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0667.62018
MathSciNet: MR964937
Digital Object Identifier: 10.1214/aos/1176351052

Subjects:
Primary: 62F12
Secondary: 62A10, 90C15

Rights: Copyright © 1988 Institute of Mathematical Statistics

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Vol.16 • No. 4 • December, 1988
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