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On the measures of multicollinearity in least squares regression

Author

Listed:
  • Wang, Song-Gui
  • Tse, Siu-Keung
  • Chow, Shein-Chung

Abstract

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.

Suggested Citation

  • Wang, Song-Gui & Tse, Siu-Keung & Chow, Shein-Chung, 1990. "On the measures of multicollinearity in least squares regression," Statistics & Probability Letters, Elsevier, vol. 9(4), pages 347-355, April.
    • Handle: RePEc:eee:stapro:v:9:y:1990:i:4:p:347-355
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    Cited by:

    1. Agustinus Nugroho & Adrie Oktavio & Endo Wijaya Kartika, 2019. "Salesperson Deviant Behavior in Indonesian Restaurant Service Attendants," International Review of Management and Marketing, Econjournals, vol. 9(4), pages 1-6.
    2. Verlinden, B. & Duflou, J.R. & Collin, P. & Cattrysse, D., 2008. "Cost estimation for sheet metal parts using multiple regression and artificial neural networks: A case study," International Journal of Production Economics, Elsevier, vol. 111(2), pages 484-492, February.

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