A Diagnostic Measure for Influential Observations in Linear Regression

References

• Atkinson , A. C. ( 1986 ). Masking unmasked . Biometrika 73 : 533 – 541 .
   Web of Science ®Google Scholar
• Atkinson , A. C. , Riani , M. ( 2000 ). Robust Diagnostic Regression Analysis . New York : Springer .
   Google Scholar
• Belsley , D. A. , Kuh , E. , Welsch , R. E. ( 1980 ). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity . New York : Wiley .
   Google Scholar
• Billor , N. , Hadi , A. S. , Velleman , F. ( 2000 ). BACON: Blocked adaptive computationally efficient outlier nominator . Computat. Statist. Data Anal. 34 : 279 – 298 .
   Web of Science ®Google Scholar
• Chatterjee , S. , Hadi , A. S. ( 2006 ). Regression Analysis by Examples. , 4th ed. New York : Wiley .
   Google Scholar
• Cook , R. D. ( 1977 ). Detection of influential observations in linear regression . Technometrics 19 : 15 – 18 .
   Web of Science ®Google Scholar
• Cook , R. D. , Weisberg , S. ( 1982 ). Residuals and Influence in Regression . London : Chapman and Hall .
   Google Scholar
• Davies , P. , Imon , A. H. M. R. , Ali , M. M. ( 2004 ). A conditional expectation method for improved residual estimation and outlier identification in linear regression . Int. J. Statist. Sci. (Special issue in honour of Professor M. S. Huq) . 191 – 208 .
   Google Scholar
• Draper , N. R. , John , J. A. ( 1981 ). Influential observations and outliers in regression . Technometrics 23 : 21 – 26 .
   Web of Science ®Google Scholar
• Habshah , M. , Norazan , R. , Imon , A. H. M. R. ( 2009 ). The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression . J. Appl. Statist. 36 : 507 – 520 .
   Web of Science ®Google Scholar
• Hadi , A. S. , Simonoff , J. S. (1993). Procedure for the identification of outliers in linear models. J. Amer. Statist. Assoc. 88:1264–1272.
   Web of Science ®Google Scholar
• Hawkins , D. M. , Bradu , D. , Kass , G. V. ( 1984 ). Location of several outliers in multiple regression data using elemental sets . Technometrics 26 : 197 – 208 .
   Web of Science ®Google Scholar
• Imon , A. H. M. R. ( 2002 ). Deletion residuals and deletion weight matrices: Some of their properties and uses . Pak. J. Statist. 12 : 469 – 484 .
   Google Scholar
• Imon , A. H. M. R. ( 2005 ). Identifying multiple influential observations in linear regression . J. Appl. Statist. 32 : 929 – 946 .
   Web of Science ®Google Scholar
• Montgomery , D. C. , Peck , E. A. , Vining , G. G. ( 2001 ). Introduction to Linear Regression Analysis. , 3rd ed. New York : Wiley .
   Google Scholar
• Pena , D. ( 2005 ). A new statistic for influence in linear regression . Technometrics 47 : 1 – 12 .
   Web of Science ®Google Scholar
• Pena , D. , Yohai , V. J. ( 1995 ). The detection of influential subsets in linear regression by using an influence matrix . J. Roy. Statist. Soc. Series B 57 : 145 – 156 .
   Google Scholar
• Pregibon , D. ( 1981 ). Logistic regression diagnostics . Ann. of Statist. 9 : 977 – 986 .
   Web of Science ®Google Scholar
• Rousseeuw , P. J. ( 1984 ). Least median of squares regression . J. Amer. Statist. Assoc. 79 : 871 – 880 .
   Web of Science ®Google Scholar
• Rousseeuw , P. J. , Leroy , A. ( 1987 ). Robust Regression and Outlier Detection . New York : Wiley .
   Google Scholar
• Simonoff , J. S. ( 1991 ). General approaches to stepwise identification of unusual values in data analysis . In: Stahel , W. , Weisberg , S. , eds. Robust Statistics and Diagnostics: Part II . New York : Springer Verlag , pp. 223 – 242 .
   Google Scholar
• Welsch , R. E. ( 1982 ). Influence functions and regression diagnostics . In: Launer , R. L. , Siegel , A. F. eds. Modern Data Analysis . New York : Academic Press .
   Google Scholar