Influence Analysis of Constrained Regression Models



Kim, Myung-Geun

  • 발행 : 2007.08.31


Cook's distance is generalized to the multiple linear regression with linear constraints on regression coefficients. It is used for identifying influential observations in constrained regression models. A numerical example is provided for illustration.


Constrained regression;Cook's distance;influence


  1. Barnett, V. and Lewis, T. (1994). Outliers in Statistical Data. 3rd ed., John Wiley & Sons, New York
  2. Chatterjee, S. and Hadi, A. S. (1986). Influential observations, high leverage points, and outliers in linear regression (with discussions). Statistical Science, 1, 379-416
  3. Cook, R. D. (1977). Detection of influential observations in linear regression. Technometrics, 19, 15-18
  4. Cook, R. D. and Weisberg, S. (1982). Residuals and Influence in Regression. Chapman & Hall, New York
  5. Kim, M. G. (2003). Detection of outliers in constrained regression. The Korean Communications in Statistics, 10, 519-524
  6. Lee, S. -Y. and Wang, S. J. (1996). Sensitivity analysis of structural equation models. Psychomeirika, 61, 93-108
  7. Neter, J., Kutner, M. H., Nachtsheim, C. J. and Wasserman, W. (1996). Applied Linear Regression Models. 3rd ed., McGraw-Hill/Irwin
  8. Paula, G. A. (1993). Assessing local influence in restricted regression models. Computational Statistics & Data Analysis, 16, 63-79
  9. Paula, G. A. (1999). Leverage in inequality-constrained regression models. The Statistician, 48, 529-538
  10. Schott, J. R. (1997). Matrix Analysis for statistics. John Wiley & Sons, New York
  11. Seber, G. A. F. (1977). Linear Regression Analysis. John Wiley & Sons, New York
  12. Chipman, J. S. and Rao, M. M. (1964). The treatment of linear restrictions in regression analysis. Econometrica, 32, 198-209

피인용 문헌

  1. 1. Influence diagnostics in constrained general linear models vol.45, pp.18, 2016, doi:10.5351/CKSS.2007.14.2.281