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July, 1976 Strong Consistency of Least Squares Estimates in Normal Linear Regression
T. W. Anderson, John B. Taylor
Ann. Statist. 4(4): 788-790 (July, 1976). DOI: 10.1214/aos/1176343552

Abstract

In the usual linear regression model the sample regression coefficients converge with probability one to the population regression coefficients when the dependent variables are normally distributed and the inverse of the second-order moment matrix of the independent variables converges to the zero matrix.

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T. W. Anderson. John B. Taylor. "Strong Consistency of Least Squares Estimates in Normal Linear Regression." Ann. Statist. 4 (4) 788 - 790, July, 1976. https://doi.org/10.1214/aos/1176343552

Information

Published: July, 1976
First available in Project Euclid: 12 April 2007

zbMATH: 0339.62039
MathSciNet: MR415899
Digital Object Identifier: 10.1214/aos/1176343552

Subjects:
Primary: 62J05
Secondary: 60F15

Keywords: least squares estimates , Linear regression , strong consistency

Rights: Copyright © 1976 Institute of Mathematical Statistics

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Vol.4 • No. 4 • July, 1976
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