MEASURE OF MULTICOLLINEARITY WITH A NEW, ORIGINAL INDICATOR (PETRES’ RED) IN LINEAR REGRESSION MODELS
MEASURE OF MULTICOLLINEARITY WITH A NEW, ORIGINAL INDICATOR (PETRES’ RED) IN LINEAR REGRESSION MODELS

Summary/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).

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