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June 1996 Asymptotics of least-squares estimators for constrained nonlinear regression
Jinde Wang
Ann. Statist. 24(3): 1316-1326 (June 1996). DOI: 10.1214/aos/1032526971


This paper is devoted to studying the asymptotic behavior of LS-estimators in constrained nonlinear regression problems. Here the constraints are given by nonlinear equalities and inequalities. Thus this is a very general setting. Essentially this kind of estimation problem is a stochastic optimization problem. So we make use of methods in optimization to overcome the difficulty caused by nonlinearity in the regression model and given constraints.


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Jinde Wang. "Asymptotics of least-squares estimators for constrained nonlinear regression." Ann. Statist. 24 (3) 1316 - 1326, June 1996.


Published: June 1996
First available in Project Euclid: 20 September 2002

zbMATH: 0862.62057
MathSciNet: MR1401852
Digital Object Identifier: 10.1214/aos/1032526971

Primary: 62J02
Secondary: 62J12

Keywords: asymptotics , LS-estimator , nonlinear constraints , Nonlinear regression , stochastic optimization

Rights: Copyright © 1996 Institute of Mathematical Statistics

Vol.24 • No. 3 • June 1996
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