The Annals of Statistics

Asymptotic Properties of Least-Squares Estimates in Stochastic Regression Models

C. Z. Wei

Full-text: Open access

Abstract

Strong consistency of least-squares estimates in stochastic regression models is established under the assumption that the underlying model can be reparametrized so that the new design vectors are weakly correlated. An application to fixed-width interval estimation in stochastic approximation schemes is also discussed.

Article information

Source
Ann. Statist., Volume 13, Number 4 (1985), 1498-1508.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349751

Digital Object Identifier
doi:10.1214/aos/1176349751

Mathematical Reviews number (MathSciNet)
MR811506

Zentralblatt MATH identifier
0582.62062

JSTOR
links.jstor.org

Subjects
Primary: 62J05: Linear regression
Secondary: 62L20: Stochastic approximation

Keywords
Stochastic regressors least squares stochastic approximation strong consistency martingales

Citation

Wei, C. Z. Asymptotic Properties of Least-Squares Estimates in Stochastic Regression Models. Ann. Statist. 13 (1985), no. 4, 1498--1508. doi:10.1214/aos/1176349751. https://projecteuclid.org/euclid.aos/1176349751


Export citation