메뉴 건너뛰기




Volumn 104, Issue 488, 2009, Pages 1671-1681

p-Values for high-dimensional regression

Author keywords

Data splitting; False discovery rate; Family wise error rate; High dimensional variable selection; Multiple comparisons

Indexed keywords


EID: 74049114503     PISSN: 01621459     EISSN: None     Source Type: Journal    
DOI: 10.1198/jasa.2009.tm08647     Document Type: Article
Times cited : (392)

References (24)
  • 2
    • 0001677717 scopus 로고
    • Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
    • Benjamini, Y., and Hochberg, Y. (1995), "Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing," Journal of the Royal Statistical Society, Ser. B, 57, 289-300.
    • (1995) Journal of the Royal Statistical Society, Ser. B , vol.57 , pp. 289-300
    • Benjamini, Y.1    Hochberg, Y.2
  • 3
    • 0035733108 scopus 로고    scopus 로고
    • The Control of the False Discovery Rate in Multiple Testing Under Dependency
    • Benjamini, Y., and Yekutieli, D. (2001), "The Control of the False Discovery Rate in Multiple Testing Under Dependency," The Annals of Statistics, 29, 1165-1188.
    • (2001) The Annals of Statistics , vol.29 , pp. 1165-1188
    • Benjamini, Y.1    Yekutieli, D.2
  • 4
    • 68649086910 scopus 로고    scopus 로고
    • Simultaneous Analysis of Lasso and Dantzig Selector
    • Bickel, P., Ritov, Y., and Tsybakov, A. (2009), "Simultaneous Analysis of Lasso and Dantzig Selector," The Annals of Statistics, 37, 1705-1732.
    • (2009) The Annals of Statistics , vol.37 , pp. 1705-1732
    • Bickel, P.1    Ritov, Y.2    Tsybakov, A.3
  • 5
    • 73949091801 scopus 로고    scopus 로고
    • Two Simple Sufficient Conditions for FDR Control
    • Blanchard, G., and Roquain, E. (2008), "Two Simple Sufficient Conditions for FDR Control," Electronic Journal of Statistics, 2, 963-992.
    • (2008) Electronic Journal of Statistics , vol.2 , pp. 963-992
    • Blanchard, G.1    Roquain, E.2
  • 6
    • 33745157294 scopus 로고    scopus 로고
    • Boosting for High-Dimensional Linear Models
    • Bühlmann, P. (2006), "Boosting for High-Dimensional Linear Models," The Annals of Statistics, 34, 559-583.
    • (2006) The Annals of Statistics , vol.34 , pp. 559-583
    • Bühlmann, P.1
  • 7
    • 0037453009 scopus 로고    scopus 로고
    • Integrating Regulatory Motif Discovery and Genome-Wide Expression Analysis
    • Conlon, E., Liu, X., Lieb, J., and Liu, J. (2003), "Integrating Regulatory Motif Discovery and Genome-Wide Expression Analysis," Proceedings of the National Academy of Science, 100, 3339-3344.
    • (2003) Proceedings of the National Academy of Science , vol.100 , pp. 3339-3344
    • Conlon, E.1    Liu, X.2    Lieb, J.3    Liu, J.4
  • 8
    • 53849086824 scopus 로고    scopus 로고
    • Sure Independence Screening for Ultra-High Dimensional Feature Space
    • Fan, J., and Lv, J. (2008), "Sure Independence Screening for Ultra-High Dimensional Feature Space," Journal of the Royal Statistical Society, Ser. B, 70, 849-911.
    • (2008) Journal of the Royal Statistical Society, Ser. B , vol.70 , pp. 849-911
    • Fan, J.1    Lv, J.2
  • 9
    • 0035470889 scopus 로고    scopus 로고
    • Greedy Function Approximation: A Gradient Boosting Machine
    • Friedman, J. (2001), "Greedy Function Approximation: A Gradient Boosting Machine," The Annals ofStatistics, 29, 1189-1232.
    • (2001) The Annals ofStatistics , vol.29 , pp. 1189-1232
    • Friedman, J.1
  • 10
    • 45849134070 scopus 로고    scopus 로고
    • Sparse Inverse Covariance Estimation With the Graphical Lasso
    • Friedman, J., Hastie, T., and Tibshirani, R. (2008), "Sparse Inverse Covariance Estimation With the Graphical Lasso," Biostatistics, 9, 432.
    • (2008) Biostatistics , vol.9 , pp. 432
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 11
    • 0002294347 scopus 로고
    • A Simple Sequentially Rejective Multiple Test Procedure
    • Holm, S. (1979), "A Simple Sequentially Rejective Multiple Test Procedure," Scandinavian Journal of Statistics, 6, 65-70.
    • (1979) Scandinavian Journal of Statistics , vol.6 , pp. 65-70
    • Holm, S.1
  • 12
    • 49849092907 scopus 로고    scopus 로고
    • Simultaneous Inference in General Parametric Models
    • Hothorn, T., Bretz, F., and Westfall, P. (2008), "Simultaneous Inference in General Parametric Models," Biometrical Journal, 50, 346-363.
    • (2008) Biometrical Journal , vol.50 , pp. 346-363
    • Hothorn, T.1    Bretz, F.2    Westfall, P.3
  • 13
    • 51049096710 scopus 로고    scopus 로고
    • Adaptive Lasso for Sparse High- Dimensional Regression Models
    • Huang, J., Ma, S., and Zhang, C.-H. (2008), "Adaptive Lasso for Sparse High- Dimensional Regression Models," Statistica Sinica, 18, 1603-1618.
    • (2008) Statistica Sinica , vol.18 , pp. 1603-1618
    • Huang, J.1    Ma, S.2    Zhang, C.-H.3
  • 15
    • 33747163541 scopus 로고    scopus 로고
    • High-Dimensional Graphs and Variable Selection With the Lasso
    • Meinshausen, N., and Bühlmann, P. (2006), "High-Dimensional Graphs and Variable Selection With the Lasso," The Annals of Statistics, 34, 1436-1462.
    • (2006) The Annals of Statistics , vol.34 , pp. 1436-1462
    • Meinshausen, N.1    Bühlmann, P.2
  • 17
    • 65349193793 scopus 로고    scopus 로고
    • Lasso-Type Recovery of Sparse Representations for High-Dimensional Data
    • Meinshausen, N., and Yu, B. (2009), "Lasso-Type Recovery of Sparse Representations for High-Dimensional Data," The Annals of Statistics, 37, 246-270.
    • (2009) The Annals of Statistics , vol.37 , pp. 246-270
    • Meinshausen, N.1    Yu, B.2
  • 19
    • 64649083745 scopus 로고    scopus 로고
    • Signal Recovery From Random Measurements via Orthogonal Matching Pursuit
    • Tropp, J., and Gilbert, A. (2007), "Signal Recovery From Random Measurements via Orthogonal Matching Pursuit," IEEE Transactions on Information Theory, 53 (12), 4655-4666.
    • (2007) IEEE Transactions on Information Theory , vol.53 , Issue.12 , pp. 4655-4666
    • Tropp, J.1    Gilbert, A.2
  • 20
    • 51049121146 scopus 로고    scopus 로고
    • High-Dimensional Generalized Linear Models and the Lasso
    • van de Geer, S. (2008), "High-Dimensional Generalized Linear Models and the Lasso," The Annals of Statistics, 36, 614-645.
    • (2008) The Annals of Statistics , vol.36 , pp. 614-645
    • van de Geer, S.1
  • 21
    • 69049091975 scopus 로고    scopus 로고
    • High Dimensional Variable Selection
    • Wasserman, L., and Roeder, K. (2009), "High Dimensional Variable Selection," The Annals of Statistics, 37, 2178-2201.
    • (2009) The Annals of Statistics , vol.37 , pp. 2178-2201
    • Wasserman, L.1    Roeder, K.2
  • 22
    • 50949096321 scopus 로고    scopus 로고
    • The Sparsity and Bias of the Lasso Selection in High-Dimensional Linear Regression
    • Zhang, C.-H., and Huang, J. (2008), "The Sparsity and Bias of the Lasso Selection in High-Dimensional Linear Regression," The Annals of Statistics, 36, 1567-1594.
    • (2008) The Annals of Statistics , vol.36 , pp. 1567-1594
    • Zhang, C.-H.1    Huang, J.2
  • 23
    • 33845263263 scopus 로고    scopus 로고
    • On Model Selection Consistency of Lasso
    • Zhao, P., and Yu, B. (2006), "On Model Selection Consistency of Lasso," Journal of Machine Learning Research, 7, 2541-2563.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2541-2563
    • Zhao, P.1    Yu, B.2
  • 24


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.