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Volumn 36, Issue 4, 2008, Pages 1595-1618

"Preconditioning" for feature selection and regression in high-dimensional problems

Author keywords

Lasso; Model selection; Prediction error

Indexed keywords


EID: 51049112528     PISSN: 00905364     EISSN: None     Source Type: Journal    
DOI: 10.1214/009053607000000578     Document Type: Article
Times cited : (91)

References (20)
  • 1
    • 33645527646 scopus 로고    scopus 로고
    • Prediction by supervised principal components
    • MR2252436
    • BAIR, E., HASTIE, T., PAUL, D. and TIBSHIRANI, R. (2006). Prediction by supervised principal components. J. Amer. Statist. Assoc. 101 119-137. MR2252436
    • (2006) J. Amer. Statist. Assoc , vol.101 , pp. 119-137
    • BAIR, E.1    HASTIE, T.2    PAUL, D.3    TIBSHIRANI, R.4
  • 2
    • 19344375744 scopus 로고    scopus 로고
    • Semi-supervised methods to predict patient survival from gene expression data
    • BAIR, E. and TIBSHIRANI, R. (2004). Semi-supervised methods to predict patient survival from gene expression data. PLOS Biology 2 511-522.
    • (2004) PLOS Biology , vol.2 , pp. 511-522
    • BAIR, E.1    TIBSHIRANI, R.2
  • 3
    • 51049095271 scopus 로고    scopus 로고
    • 1-norm solution is the sparsest solution. Technical report, Stanford Univ.
    • 1-norm solution is the sparsest solution. Technical report, Stanford Univ.
  • 5
    • 3242708140 scopus 로고    scopus 로고
    • Least angle regression (with discussion)
    • MR2060166
    • EFRON, B., HASTIE, T., JOHNSTONE, I. and TIBSHIRANI, R. (2004). Least angle regression (with discussion). Ann. Statist. 32 407-499. MR2060166
    • (2004) Ann. Statist , vol.32 , pp. 407-499
    • 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
    • MR1946581
    • FAN, J. and LI, R. (2005). Variable selection via nonconcave penalized likelihood, and its oracle properties. J. Amer. Statist. Assoc. 96 1348-1360. MR1946581
    • (2005) J. Amer. Statist. Assoc , vol.96 , pp. 1348-1360
    • FAN, J.1    LI, R.2
  • 7
    • 24344502730 scopus 로고    scopus 로고
    • Nonconcave penalized, likelihood with a diverging number of parameters
    • MR2065194
    • FAN, J. and PENG, H. (2004). Nonconcave penalized, likelihood with a diverging number of parameters. Ann. Statist. 32 928-961. MR2065194
    • (2004) Ann. Statist , vol.32 , pp. 928-961
    • FAN, J.1    PENG, H.2
  • 8
    • 85088938629 scopus 로고    scopus 로고
    • KALBFLEISCH, J. and PRENTICE, R. (1980). The Statistical Analysis of Failure Time Data. Wiley, New York. MR0570114
    • KALBFLEISCH, J. and PRENTICE, R. (1980). The Statistical Analysis of Failure Time Data. Wiley, New York. MR0570114
  • 9
    • 0034287156 scopus 로고    scopus 로고
    • Asymptotics for lasso-type estimators
    • MR1805787
    • KNIGHT, K. and FU, W. (2000). Asymptotics for lasso-type estimators. Ann. Statist. 28 1356-1378. MR1805787
    • (2000) Ann. Statist , vol.28 , pp. 1356-1378
    • KNIGHT, K.1    FU, W.2
  • 10
    • 51049106110 scopus 로고    scopus 로고
    • Lasso with relaxation
    • ETH Zürich
    • MEINSHAUSEN, M. (2005). Lasso with relaxation. Research Report 129, ETH Zürich.
    • (2005) Research Report , vol.129
    • MEINSHAUSEN, M.1
  • 11
    • 33747163541 scopus 로고    scopus 로고
    • High-dimensional graphs and variable selection with the lasso
    • MR2278363
    • MEINSHAUSEN, N. and BÜHLMANN, P. (2006). High-dimensional graphs and variable selection with the lasso. Ann. Statist. 34 1436-1462. MR2278363
    • (2006) Ann. Statist , vol.34 , pp. 1436-1462
    • MEINSHAUSEN, N.1    BÜHLMANN, P.2
  • 13
    • 34247332440 scopus 로고    scopus 로고
    • Anil regularization-path algorithm, for generalized linear models
    • Unpublished manuscript
    • PARK, M. Y. and HASTIE, T. (2006). Anil regularization-path algorithm, for generalized linear models. Unpublished manuscript.
    • (2006)
    • PARK, M.Y.1    HASTIE, T.2
  • 15
    • 0036489055 scopus 로고    scopus 로고
    • Adaptive model selection
    • MR1947281
    • SHEN, X. and YE, J. (2002). Adaptive model selection. J. Amer. Statist. Assoc. 97 210-221. MR1947281
    • (2002) J. Amer. Statist. Assoc , vol.97 , pp. 210-221
    • SHEN, X.1    YE, J.2
  • 16
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • MR1379242
    • TIBSHIRANI, R. (1996). Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B 58 267-288. MR1379242
    • (1996) J. Roy. Statist. Soc. Ser. B , vol.58 , pp. 267-288
    • TIBSHIRANI, R.1
  • 17
    • 0037076272 scopus 로고    scopus 로고
    • Diagnosis of multiple cancer types by shrunken centroids of gene expression
    • TIBSHIRANI, R., HASTIE, T., NARASIMHAN, B. and CHU, G. (2001). Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99 6567-6572.
    • (2001) Proc. Natl. Acad. Sci. USA , vol.99 , pp. 6567-6572
    • TIBSHIRANI, R.1    HASTIE, T.2    NARASIMHAN, B.3    CHU, G.4
  • 18
    • 32144434202 scopus 로고    scopus 로고
    • Gene expression profiling predicts survival in conventional renal cell carcinoma
    • ZHAO, H., TIBSHIRANI, R. and BROOKS, J. (2005). Gene expression profiling predicts survival in conventional renal cell carcinoma. PloS. Med. 3(1) e13.
    • (2005) PloS. Med , vol.3 , Issue.1
    • ZHAO, H.1    TIBSHIRANI, R.2    BROOKS, J.3
  • 19
    • 33845263263 scopus 로고    scopus 로고
    • On model selection consistency of Lasso
    • MR2274449
    • ZHAO, P. and YU, B. (2006). On model selection consistency of Lasso. J. Mach. Learn. Res. 7 2541-2563. MR2274449
    • (2006) J. Mach. Learn. Res , vol.7 , pp. 2541-2563
    • ZHAO, P.1    YU, B.2
  • 20
    • 33846114377 scopus 로고    scopus 로고
    • The adaptive lasso and its oracle properties
    • MR2279469
    • ZOU, H. (2005). The adaptive lasso and its oracle properties. J. Amer. Statist. Assoc. 101 1418-1429. MR2279469
    • (2005) J. Amer. Statist. Assoc , vol.101 , pp. 1418-1429
    • ZOU, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.