On the measures of multicollinearity in least squares regression

For a general regression model y = X[beta] + e, E(e) = 0, Cov(e) = [sigma]2V-1, some results on the relationship between two measures of multicollinearity, the eigenvalues and the condition numbers of X'X and X'VX, are obtained. These results are useful in examining the effects of augmentation of data on multicollinearity and the influence of an observation on the condition number of X'X in regression diagnostics.

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Year of publication:	1990
Authors:	Wang, Song-Gui ; Tse, Siu-Keung ; Chow, Shein-Chung
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 9.1990, 4, p. 347-355
Publisher:	Elsevier
Keywords:	Multicollinearity condition number generalized least squares data augmentation regression diagnostic

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005223841