Journal
COMPUTATIONAL ECONOMICS
Volume 57, Issue 2, Pages 529-536Publisher
SPRINGER
DOI: 10.1007/s10614-019-09967-y
Keywords
Multicollinearity; Detection; Intercept; Dummy; Software
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This paper introduces a newRpackagemultiColl for detecting near collinearity in linear regression models, which overcomes the shortcomings observed in existing software packages related to the treatment of independent qualitative variables and the role of the intercept in the model.
The detection of problematic collinearity in a linear regression model is treated in all the existing statistical software packages. However, such detection is not always done adequately. The main shortcomings relate to treatment of independent qualitative variables and completely ignoring the role of the intercept in the model (consequently, ignoring the nonessential collinearity). This paper presents theRpackagemultiColl, which implements the usually applied measures for detecting near collinearity while overcoming the weaknesses observed in other existing packages.
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