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June 2000 Strong consistency in nonlinear stochastic regression models
K. Skouras
Ann. Statist. 28(3): 871-879 (June 2000). DOI: 10.1214/aos/1015952002

Abstract

The class of nonlinear stochastic regression models includes most of the linear and nonlinear models used in time series, stochastic control and stochastic approximation schemes.The consistency of least squares estimators was established first by Lai.We present another set of sufficient conditions for consistency, which avoid the use of partial derivatives and are closer in spirit to the conditions presented by Wu for non-stochastic regression models with independent errors.

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K. Skouras. "Strong consistency in nonlinear stochastic regression models." Ann. Statist. 28 (3) 871 - 879, June 2000. https://doi.org/10.1214/aos/1015952002

Information

Published: June 2000
First available in Project Euclid: 12 March 2002

zbMATH: 1105.62355
MathSciNet: MR1792791
Digital Object Identifier: 10.1214/aos/1015952002

Subjects:
Primary: 62J02
Secondary: 60F15 , 62F12 , 62M10

Keywords: consistency , least squares estimator , martingale , stochastic regression

Rights: Copyright © 2000 Institute of Mathematical Statistics

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Vol.28 • No. 3 • June 2000
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