Classical studies that revolutionized the practice of regression analysis

Technometrics

Volumn 42, Issue 1, 2000, Pages 62-64

  Gunst, Richard F ^a  

^a SOUTHERN METHODIST UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION; LEAST SQUARES APPROXIMATIONS;

REGRESSION COEFFICIENT ESTIMATES;

REGRESSION ANALYSIS;

EID: 0033906921     PISSN: 00401706     EISSN: 15372723     Source Type: Journal    
DOI: 10.1080/00401706.2000.10485980     Document Type: Article

References (26)

1. Beckman, R. J., and Trussell, H. J. (1974), “The Distribution of an Arbitrary Studentized Residual and the Effects of Updating in Multiple Regression,” Journal of the American Statistical Association, 69, 199-201.
2. Behnken, D. W., and Draper, N. R. (1972), “Residuals and Their Variance Patterns,” Technometrics, 14, 102-111.
3. Conniffe, D., and Stone, J. (1973), “A Critical View of Ridge Regression,” The Statistician, 22, 181-187.
4. Cook, R. D. (1977), “Detection of Influential Observations in Regression,” Technometrics, 19, 15-18.
5. Daniel, C., and Wood, F. (1971), Fitting Equations to Data, New York: Wiley.
6. Dempster, A. P., Schatzoff, M., and Wermuth, N. (1977), “A Simulation Study of Alternatives to Ordinary Least Squares,” Journal of the American Statistical Association, 72, 77-90.
7. Draper, N., and Smith, H. (1998), Applied Regression Analysis (3rd ed.), New York: Wiley.
8. Draper, N., and Van Nostrand, R. C. (1979), “Ridge Regression and JamesStein Estimation: Review and Comments,” Technometrics, 21, 451-466.
9. Furnival, G. M. (1971), “All Possible Regressions With Less Computation,” Technometrics, 13, 403-408.
10. Furnival, G. M., and Wilson, R. W., Jr. (1974), “Regression by Leaps and Bounds,” Technometrics, 16, 499-511.
11. Goodnight, J. H. (1979), “A Tutorial on the SWEEP Operator,” The American Statistician, 33, 149-158.
12. Gorman, J. W., and Toman, R. J. (1966), “Selection of Variables for Fitting Equations to Data,” Technometrics, 8, 27-51.
13. Hoaglin, D. C., and Welsch, R. (1978), “The Hat Matrix in Regression and ANOVA,” The American Statistician, 32, 17-22.
14. Hocking, R. R., and Leslie, R. N. (1967), “Selection of the Best Subset in Regression Analysis,” Technometrics, 9, 531-540.
15. Hoerl, A. E. (1962), “Application of Ridge Analysis to Regression Problems,” Chemical Engineering Progress, 58, 54-59.
16. Hoerl, A. E., and Kennard, R. W. (1970a), “Ridge Regression: Biased Estimation for Nonorthogonal Problems,” Technometrics, 12, 55-67.
17. Hoerl, A. E., and Kennard, R. W. (1970b), “Ridge Regression: Applications to Nonorthogonal Problems,” Technometrics, 12, 69-82.
18. Hoerl, A. E., Kennard, R. W., and Baldwin, K. F. (1975), “Ridge Regression: Some Simulations,” Communications in Statistics, Part A—Theory and Methods, 4, 105-123.
19. LaMotte, L. R., and Hocking, R. R. (1970), “Computational Efficiency in the Selection of Regression Variables,” Technometrics, 12, 83-93.
20. Longley, J. W. (1967), “An Appraisal of Least Squares Programs for the Electronic Computer From the Point of View of the User,” Journal of the American Statistical Association, 62, 819-841.
21. p,” Technometrics, 15, 661-675.
22. Marquardt, D. W. (1970), “Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation,” Technometrics, 12, 591-612.
23. Neider, J. A. (1972), “Discussion of a Paper by D. V. Lindley and A. F. M. Smith,” Journal of the Royal Statistical Society, Ser. B, 34, 18-20.
24. SAS Institute Inc. (1990), SAS/STAT User’s Guide, Version 6 (4th ed., vol. 2), Cary, NC: Author.
25. Schatzoff, M., Feinberg, S., and Tsao, R. (1968), “Efficient Calculation of All Possible Regressions,” Technometrics, 10, 769-779.
26. Theobald, C. M. (1974), “Generalizations of Mean Squared Error Applied to Ridge Regression,” Journal of the Royal Statistical Society, Ser. B, 36, 103-106.