The adaptive lasso and its oracle properties

Cited by (1,004)

Items 401–500 of 1,004

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    Tianxi Cai, Jian Huang, Lü Tian · 2008 · Biometrics
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56. Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM
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57. NONCONCAVE PENALIZED M-ESTIMATION WITH A DIVERGING NUMBER OF PARAMETERS
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    Peng Zhao, Bin Yu · 2007
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    Patrick John Breheny · 2015 · Biometrics
61. Consistent model selection criteria on high dimensions
    Yongdai Kim, Sunghoon Kwon, Hosik Choi · 2012
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63. Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso
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    Heng Peng, Tao Huang · 2010 · Journal of Statistical Planning and Inference
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    Xun Lu, Liangjun Su · 2015 · Journal of Econometrics
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83. Rates of convergence of the Adaptive LASSO estimators to the Oracle distribution and higher order refinements by the bootstrap
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    A. Benner, M. Zucknick, T. Hielscher, C. Ittrich, U. Mansmann · 2010 · Biometrical journal. Biometrische Zeitschrift
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