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February, 1987 Collinearity and Least Squares Regression
G. W. Stewart
Statist. Sci. 2(1): 68-84 (February, 1987). DOI: 10.1214/ss/1177013439

Abstract

In this paper we introduce certain numbers, called collinearity indices, which are useful in detecting near collinearities in regression problems. The coefficients enter adversely into formulas concerning significance testing and the effects of errors in the regression variables. Thus they provide simple regression diagnostics, suitable for incorporation in regression packages.

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G. W. Stewart. "Collinearity and Least Squares Regression." Statist. Sci. 2 (1) 68 - 84, February, 1987. https://doi.org/10.1214/ss/1177013439

Information

Published: February, 1987
First available in Project Euclid: 19 April 2007

zbMATH: 0643.62049
MathSciNet: MR896260
Digital Object Identifier: 10.1214/ss/1177013439

Keywords: collinearity , errors in the variables , ill-conditioning , Linear regression , regression diagnostics

Rights: Copyright © 1987 Institute of Mathematical Statistics

Vol.2 • No. 1 • February, 1987
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