International Statistical Review

A New Measure of Multicollinearity in Linear Regression Models

Péter Kovács, Tibor Petres, and László Tóth

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Abstract

Databases with a lot of data very often mean little information. It is because of the collinearity of variables which consist of the data of the database. This collinearity is in fact a kind of redundancy of the database. In the study a new indicator is given. With this indicator, which contains the eigenvalues of the variables' correlation matrix, it is possible to quantify the percentage of collinearity: from 0% (all the eigenvalues are equal to 1) to 100% (all the eigenvalues, except the first, are equal to 0).

Article information

Source
Internat. Statist. Rev., Volume 73, Number 3 (2005), 405-412.

Dates
First available in Project Euclid: 5 December 2005

Permanent link to this document
https://projecteuclid.org/euclid.isr/1133819161

Zentralblatt MATH identifier
1105.62072

Keywords
Redundancy of databases Multicollinearity Spectral decomposition of the correlation matrix

Citation

Kovács, Péter; Petres, Tibor; Tóth, László. A New Measure of Multicollinearity in Linear Regression Models. Internat. Statist. Rev. 73 (2005), no. 3, 405--412. https://projecteuclid.org/euclid.isr/1133819161


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References

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