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The Metric Number and Non-essential Approximate Multicollinearity

In: Advances in Quantitative Methods for Economics and Business

Author

Listed:
  • Román Salmerón Gómez

    (University of Granada)

  • Catalina B. García-García

    (Polígono La Cartuja, s/n)

  • Donald Ramírez

    (University of Virginia)

Abstract

Within the possible linear relationships that can exist in a multiple linear regression model (multicollinearity), one relationship that is often overlooked is the one between the constant term of the model and the rest of the independent variables. This type of approximate multicollinearity is ignored by the variance inflation factor while it can be detected through the condition number or the coefficient of variation. In this work, the utility of the metric number is analyzed for detecting this type of approximate multicollinearity from a geometric perspective.

Suggested Citation

  • Román Salmerón Gómez & Catalina B. García-García & Donald Ramírez, 2025. "The Metric Number and Non-essential Approximate Multicollinearity," Springer Books, in: Salvador Cruz Rambaud & Juan Evangelista Trinidad Segovia & Catalina B. García-García (ed.), Advances in Quantitative Methods for Economics and Business, chapter 0, pages 79-98, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-84782-0_5
    DOI: 10.1007/978-3-031-84782-0_5
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