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Technometrics Volume 16, 1974 - Issue 2
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NOTES

Approximating the Distribution of the Sample R2 in Best Subset Regressions

George Diehr Graduate School of Business Administration, University of Washington, Seattle, Washington
&
Donald R. Hoflin Graduate School of Business Administration, University of Washington, Seattle, Washington
Pages 317-320 | Published online: 09 Apr 2012

References

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  • Beale , E. M. L. , Kendall , M. G. and Mann , D. W. 1967 . The discarding of variables in multivariate analysis . Biometrika , 54 : 357 – 366 .
  • Draper , N. R. and Smith , H. 1966 . Applied Regression Analysis New York : John Wiley and Sons, Inc. .
  • Effroymson , M. A. 1960 . “ Multiple regression analysis. ” . In Mathematical Methods for Digital Computers Edited by: Ralson , A. and Wilf , H. S. New York : John Wiley and Sons, Inc. .
  • Furnival , G. M. 1971 . All possible regressions with less computation . Technometrics , 13 : 403 – 408 .
  • Garside , M. J. 1971 . Some computations procedures for the best subset problem . Applied Statistics , 20 : 8 – 15 .
  • Hocking , R. R. and Leslie , N. N. 1967 . Selection of the best subset in regression analysis . Technometrics , 9 : 531 – 540 .
  • Lachenbruch , P. A. 1968 . On expected probability of misclassification in discriminant analysis, necessary sample size, and a relation with the multiple correlation coefficient . Biometrics , 24 : 823 – 834 .
  • Mantel , N. 1970 . Why stepdown procedures in variable selection . Technometrics , 12 : 621 – 625 .
  • Schatzoff , M. , Fienberg , S. and Tsao , R. 1968 . Efficient calculations of all possible regressions . Technometrics , 10 : 768 – 799 .

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