Influential subsets on the variable selection

Communications in Statistics Part B: Simulation and Computation

Volumn 29, Issue 2, 2000, Pages 335-347

  Kim, Choongrak ^a,b   Hwang, Soonyoung ^a  

^a Pusan National University   (South Korea)

^b Research Institute of Computer Information and Communication   (South Korea)

Author keywords

Influential observation; Mallows' C p; Masking effect

Indexed keywords

EID: 0043111985     PISSN: 03610918     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (24)

1. Allen, D.M. (1971) Mean square error of prediction as a criterion for selecting variables, Technometrics, 13, 469-475.
2. Andrews, D.F. and Pregibon, D. (1978) Finding outliers that matter, Journal of the Royal Statistical Society, Ser. B, 40, 85-93.
3. Breiman, L. (1992) The little bootstrap and other methods for dimensionality selection in regression : X-fixed prediction error, Journal of the American Statistical Association, 87, 738-754.
4. Chatterjee, S. and Hadi, A.S. (1988) Impact of simultaneous omission of a variable and an observation on a linear regression equation, Computational Statistics and Data Analysis, 6, 129-144.
5. Cook, R. D. (1977) Detection of influential observation in linear regression, Technometrics, 19, 15-18.
6. Cook, R. D., and Wang, P. C. (1983) Transformations and influential cases in regression, Technometrics, 25, 337-343.
7. Eubank, R. L. (1985) Diagnostics for smoothing splines, Journal of the Royal Statistical Society, Ser. B, 47, 332-341.
8. Hinkley, D. V., and Wang, S. (1988) More about transformations and influential cases in regression, Technometrics, 30, 435-440.
9. Kim, C. (1996) Local influence and replacement measure, Communications in Statistics - Theory and Methods, 25, 49-61.
10. Kim, C. (1996) Cook's distance in spline smoothing. Statistics and Probability Letters, 31 139-144.
11. Kim, C., and Storer, B. E. (1996) Reference values for Cook's distance, Communications in Statistics - Simulation and Computation, 25, 691-709.
12. Kim, C., Storer, B. E., and Jeong, M. (1996) A note on Box-Cox transformation diagnostics, Technometrics, 38, 178-180.
13. Leger, C. and Altman, N. (1993) Assessing influence in variable selection problems, Journal of the American Statistical Association, 88, 547-556.
14. p, Technometrics, 15, 661-676.
15. Miller, A. J. (1984) Selection of subsets of regression variables(with discussion), Journal of the Royal Statistical Society, Ser. A, 147, 387-425.
16. Miller, A.J. (1990) Subset Selection in Regression, Chapman and Hall, London.
17. Neter, J., Wasserman, W., and Kutner, M. H. (1990) Applied Linear Statistical Models(3rd ed.), Irwin, Homewood, IL.
18. Pregibon, D. (1981), Logistic regression diagnostics, The Annals of Statistics, 9, 705-724.
19. Shao, M. (1993) Linear model selection by cross-validation, Journal of the American Statistical Association, 88, 486-494.
20. Silverman, B. W. (1985) Some aspects of the spline smoothing approach to non-parametric regression curve fitting (with discussion), Journal of the Royal Statistical Society, Ser. B, 47, 1-52.
21. Tsai, C. L., and Wu, X. (1990) Diagnostics in transformation and weighted regression, Technometrics, 32, 3155-322.
22. Thomas, W. (1991) Influence diagnostics for the cross-validated smoothing parameter in spline smoothing, Journal of the American Statistical Association, 86, 693-698.
23. p to individual cases, Technometrics, 23, 27-31.
24. Weisberg, S. (1985) Applied Linear Regression(2nd ed.), John Wiley, New York.