메뉴 건너뛰기




Volumn 131, Issue 2, 2005, Pages 333-347

Nonlinear GCV and quasi-GCV for shrinkage models

Author keywords

Lasso; Longitudinal studies; Ridge; Standard shrinkage rate; Weighted deviance

Indexed keywords


EID: 14044256525     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jspi.2004.03.001     Document Type: Article
Times cited : (16)

References (27)
  • 2
    • 84874257732 scopus 로고
    • Better subset regression using the nonnegative garrote
    • Breiman L. Better subset regression using the nonnegative garrote Technometrics 37 1995 373-384
    • (1995) Technometrics , vol.37 , pp. 373-384
    • Breiman, L.1
  • 3
    • 34250263445 scopus 로고
    • Smoothing noisy data with spline functions
    • Craven P. Wahba G. Smoothing noisy data with spline functions Numer. Math. 31 1979 377-403
    • (1979) Numer. Math. , vol.31 , pp. 377-403
    • Craven, P.1    Wahba, G.2
  • 5
    • 0038821242 scopus 로고    scopus 로고
    • Least angle regression
    • Technical Report, Department of Statistics, Stanford University, Palo Alto, CA
    • Efron, B., Hastie, T., Johnstone, I., Tibshirani, R., 2002. Least angle regression. Technical Report, Department of Statistics, Stanford University, Palo Alto, CA.
    • (2002)
    • Efron, B.1    Hastie, T.2    Johnstone, I.3    Tibshirani, R.4
  • 6
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • Fan J. Li R. Variable selection via nonconcave penalized likelihood and its oracle properties J. Amer. Statist. Assoc. 96 2001 1348-1360
    • (2001) J. Amer. Statist. Assoc. , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 7
    • 84952149204 scopus 로고
    • A statistical view of some chemometrics regression tools
    • Frank I.E. Friedman J.H. A statistical view of some chemometrics regression tools Technometrics 35 1993 109-148
    • (1993) Technometrics , vol.35 , pp. 109-148
    • Frank, I.E.1    Friedman, J.H.2
  • 8
    • 0032361278 scopus 로고    scopus 로고
    • Penalized regressions: The Bridge versus the Lasso
    • Fu W.J. Penalized regressions: The Bridge versus the Lasso J. Comput. Graph Statist. 7 1998 397-416
    • (1998) J. Comput. Graph Statist. , vol.7 , pp. 397-416
    • Fu, W.J.1
  • 9
    • 14044262265 scopus 로고    scopus 로고
    • Ridge estimator in singular design with application to age-period-cohort analysis of disease rates
    • Fu W.J. Ridge estimator in singular design with application to age-period-cohort analysis of disease rates Comm. Statist. Theoret. Methods 29 2000 263-278
    • (2000) Comm. Statist. Theoret. Methods , vol.29 , pp. 263-278
    • Fu, W.J.1
  • 10
    • 0037366627 scopus 로고    scopus 로고
    • Penalized estimating equations
    • Fu W.J. Penalized estimating equations Biometrics 59 2003 126-132
    • (2003) Biometrics , vol.59 , pp. 126-132
    • Fu, W.J.1
  • 11
    • 14044273025 scopus 로고    scopus 로고
    • Effective number of observations for correlated data
    • Unpublished manuscript
    • Fu, W.J., 2003b. Effective number of observations for correlated data. Unpublished manuscript.
    • (2003)
    • Fu, W.J.1
  • 12
    • 32044449925 scopus 로고
    • Generalized cross-validation as a method for choosing a good ridge parameter
    • Golub G.H. Heath M. Wahba G. Generalized cross-validation as a method for choosing a good ridge parameter Technometrics 21 1979 215-223
    • (1979) Technometrics , vol.21 , pp. 215-223
    • Golub, G.H.1    Heath, M.2    Wahba, G.3
  • 13
    • 0035622815 scopus 로고    scopus 로고
    • Cross-validating non-Gaussian data: Generalized approximate cross-validation revisited
    • Gu C. Xiang D. Cross-validating non-Gaussian data: Generalized approximate cross-validation revisited J. Comput. Graph Statist. 10 2001 581-591
    • (2001) J. Comput. Graph Statist. , vol.10 , pp. 581-591
    • Gu, C.1    Xiang, D.2
  • 15
    • 0034287156 scopus 로고    scopus 로고
    • Asymptotics for Lasso-type estimators
    • Knight K. Fu W.J. Asymptotics for Lasso-type estimators Ann. Statist. 28 2000 1356-1378
    • (2000) Ann. Statist. , vol.28 , pp. 1356-1378
    • Knight, K.1    Fu, W.J.2
  • 16
    • 77649173768 scopus 로고
    • Longitudinal data analysis using generalized linear models
    • Liang K.-Y. Zeger S.L. Longitudinal data analysis using generalized linear models Biometrika 73 1986 13-22
    • (1986) Biometrika , vol.73 , pp. 13-22
    • Liang, K.-Y.1    Zeger, S.L.2
  • 17
    • 0034343415 scopus 로고    scopus 로고
    • Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV
    • Lin X. Wahba G. Xiang D. Gao F. Klein R. Klein B. Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV Ann. Statist. 28 2000 1570 1600
    • (2000) Ann. Statist. , vol.28 , pp. 1570-1600
    • Lin, X.1    Wahba, G.2    Xiang, D.3    Gao, F.4    Klein, R.5    Klein, B.6
  • 20
    • 21144474350 scopus 로고
    • Linear model selection by cross-validation
    • Shao J. Linear model selection by cross-validation J. Amer. Statist. Assoc. 88 1993 486-494
    • (1993) J. Amer. Statist. Assoc. , vol.88 , pp. 486-494
    • Shao, J.1
  • 21
    • 0642336882 scopus 로고    scopus 로고
    • An asymptotic theory for linear model selection
    • Shao J. An asymptotic theory for linear model selection Statist. Sinica 7 1997 221-264
    • (1997) Statist. Sinica , vol.7 , pp. 221-264
    • Shao, J.1
  • 22
    • 0024599612 scopus 로고
    • Prostate specific antigen in the diagnosis and treatment of adenocarcinoma of the prostate ii. radical prostatectomy treated patients
    • Stamey T. Kabalin J. McNeal J. Johnston I. Freiha F. Redwine E. Yang N. Prostate specific antigen in the diagnosis and treatment of adenocarcinoma of the prostate ii. radical prostatectomy treated patients J. Urol. 16 1989 1076-1083
    • (1989) J. Urol. , vol.16 , pp. 1076-1083
    • Stamey, T.1    Kabalin, J.2    McNeal, J.3    Johnston, I.4    Freiha, F.5    Redwine, E.6    Yang, N.7
  • 23
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the Lasso
    • Tibshirani R. Regression shrinkage and selection via the Lasso J. Roy. Statist. Soc. B 58 1996 267-288
    • (1996) J. Roy. Statist. Soc. B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 24
    • 12844270447 scopus 로고    scopus 로고
    • Sparsity and smoothness via the fused lasso
    • Technical Report, Department of Statistics, Stanford University, Palo Alto, CA
    • Tibshirani, R., Saunders, M., Rosset, S., Zhu, J., 2003. Sparsity and smoothness via the fused lasso. Technical Report, Department of Statistics, Stanford University, Palo Alto, CA.
    • (2003)
    • Tibshirani, R.1    Saunders, M.2    Rosset, S.3    Zhu, J.4
  • 26
    • 21444449622 scopus 로고    scopus 로고
    • A generalized approximate cross validation for smoothing splines with non-Gaussian data
    • Xiang D. Wahba G. A generalized approximate cross validation for smoothing splines with non-Gaussian data Statist. Sinica 6 1996 675-692
    • (1996) Statist. Sinica , vol.6 , pp. 675-692
    • Xiang, D.1    Wahba, G.2
  • 27
    • 0022673130 scopus 로고
    • Longitudinal data analysis for discrete and continuous outcomes
    • Zeger S.L. Liang K.-Y. Longitudinal data analysis for discrete and continuous outcomes Biometrics 42 1986 121-130
    • (1986) Biometrics , vol.42 , pp. 121-130
    • Zeger, S.L.1    Liang, K.-Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.