J Fan,R Li.Statistical challenges with high dimensionality:Fe-ature selection in knowledge discovery .M Sanz-Sole,J Soria,J L Varona,et al.Proceedings of the International Congress of Mathematicians Volume III .Zurich:European Mathematical Society,2006.595-622.
[2]
J Fan,J Lv.Sure independence screening for ultrahigh dimensional feature space [J].Journal of the Royal Statistical Society Series B,2008,70(5):849-911.
[3]
T Hastie,R Tibshirani,J Friedman.The Elements of Statistical Learning Data Mining,Inference,and Prediction [M].New York:Springer-Verlag,2002.61-78.
[4]
D L Donoho,J Tanner.Precise undersampling theorems [J].Proceedings of the IEEE,2010,98(6):913-924.
[5]
D L Donoho.Scanning the technology [J].Proceedings of the IEEE,2010,98(6):910-912.
[6]
J A Tropp.Just relax:Convex programming methods for identifying sparse signals in noise [J].IEEE Transactions on Information Theory,2006,52(3):1030-1051.
[7]
焦李成,杨淑媛,刘芳,等.压缩感知回顾与展望[J].电子学报,2011,39(7):1651-1622. L Jiao,S Yang,F Liu,et al.Development and prospect of compressive sensing [J].Acta Electronica Sinica,2011,39(7):1651-1622.(in Chinese)
[8]
J Fan,R Li.Variable selection via nonconcave penalized likelihood and its oracle properties [J].Journal of the American Statistical Association,2001,96(456):1348-1360.
[9]
D L Donoho.For most large underdetermined systems of equations,the minimal l1-norm near-solution approximates the sparsest near-solution [J].Communications on Pure and Applied Mathematics,2006,59(6):797-829.
[10]
M Yuan,Y Lin.Model selection and estimation in regression with grouped variables [J].Journal of the Royal Statistical Society B,2006,68(1):49-67.
[11]
H Zou,T Hastie.Regularization and variable selection via the elastic net [J].Journal of the Royal Statistical Society B,2005,67(2):301-320.
[12]
Y Liu,Y Wu.Variable selection via a combination of the L0 and L1 penalties [J].Journal of Computational and Graphical Statistics,2007,16(4):782-798.
[13]
J Guo,G James,E Levina.Principal component analysis with sparse fused loadings [J].Journal of Computational and Graphical Statistics,2010,19(4):930-946.
[14]
H Shen,J Z Huang.Sparse principal component analysis via regularized low rank matrix approximation [J].Journal of Multivariate Analysis,2008,99(6):1015-1034.
[15]
M Journee,Y Nesterov,P Richtarik.Generalized power method for sparse principal component analysis [J].Journal of Machine Learning Research,2010,11:517-553.
[16]
J O Ramsay,B W Silverman.Functional Data Analysis,2nd ed [M].New York:Springer,2005.
[17]
H L Shang.Visualizing and Forecasting Functional Time Series .Melbourne:Monash University,2010.
[18]
A Y Lu.Sparse Principal Component Analysis for Functional Data .Stanford:Stanford University,2002.
[19]
D M Witten,T Hastie,R Tibshirani.Discussion [J].Journal of the American Statistical Association,2009,104(486):698-699.
[20]
J O Ramsay.Comments [J].Journal of the American Statistical Association,2009,104(486):700-700.
[21]
I T Jolliffe.Principal Component Analysis,2nd ed [M].New York:Springer-Verlag,2002.
[22]
S Lee,F Zou,F A Wright.Convergence and prediction of principal component scores in high-dimensional settings [J].The Annals of Statistics,2010,38(6):3605-3629.
[23]
A M Bruckstein,D L Donoho,M Elad.From sparse solutions of systems of equations to sparse modeling of signals and images [J].SIAM Review,2009,51(1):34-81.
[24]
M Lustig,D Donoho,J M Pauly.Sparse MRI:The application of compressed sensing .Magnetic Resonance in Medicine,2007,58(6):1182-1195.
[25]
J Yang,Y Peng,W Xu,et al.Ways to sparse representation:An overview [J].Science in China Series F:Information Sciences,2009,52(4):695-703.
[26]
孙玉宝,吴敏,韦志辉,等.基于稀疏表示的脑电棘波检测算法研究[J].电子学报.2009,37(9):1971-1976. Y Sun,M Wu,Z Wei,et al.EEG spike detection using sparse representation [J].Acta Electronica Sinica,2009,37(9):1971-1976.(in Chinese)
[27]
J Fan,J Lv.A selective overview of variable selection in high dimensional feature space [J].Statistica Sinica,2010,20(1):101-148.
[28]
R Tibshirani.Regression shrinkage and selection via the lasso [J].Journal of the Royal Statistical Society B,1996,58(1):267-288.
[29]
R Tibshirani,M Saunders.Sparsity and smoothness via the fused lasso [J].Journal of the Royal Statistical Society B,2005,67(1):91-108.
[30]
H Zou.The adaptive lasso and its oracle properties [J].Journal of the American Statictical Association,2006,101(476):1418-1429.
[31]
H Zou,H H Zhang.On the adaptive elastic net with a diverging number of parameters [J].The Annals of Statistics,2009,37(4):1733-1751.
[32]
P Zhao,G Rocha,B Yu.The composite absolute penalties family for grouped and hierarchical variable selection [J].The Annals of Statistics,2009,37(6A):3468-3497.
[33]
G M James,P Radchenko,J Lv.DASSO:connections between the Dantzig selector and lasso [J].Journal of the Royal Statistical Society B,2009,71(1):127-142.
[34]
I T Jolliffe,N T Trendafilov,M Uddin.A modified principal component technique based on the LASSO [J].Journal of Computational and Graphical Statistics,2003,12(3):531-547.
[35]
N T Trendafilov,I T Jolliffe.Projected gradient approach to the numerical solution of the SCoTLASS [J].Computational Statistics and Data Analysis,2006,50(1):242-253.
[36]
C Leng,H Wang.On general adaptive sparse principal component analysis [J].Journal of Computational and Graphical Statistics,2009,18(1):201-215.
[37]
H Zou,T Hastie,R Tibshirani.Sparse principal component analysis [J].Journal of Computational and Graphical Statistics,2006,15(2):265-286.
[38]
D Lee,W Lee,Y Lee,et al.Super-sparse principal component analyses for high-throughput genomic data [J].BMC Bioinformatics,2010,11(1):296.
[39]
D M Witten,R Tibshirani,T Hastie.A penalized matrix decomposition,with applications to sparse principal components and canonical correlation analysis [J].Biostatistics,2009,10(3):515-534.
[40]
A d''Aspremont,L E Ghaoui,M I Jordan.A direct formulation for sparse PCA using semidefinite programming [J].SIAM Review,2007,49(3):434-448.
[41]
A A Amini,M J Wainwright.High dimensional analysis of semidefinite relaxations for sparse principal components [J].The Annals of Statistics,2009,37(5B):2877-2921.
[42]
B Efron,T Hastie,I Johnstone,R Tibshirani.Least angle regression [J].The Annals of Statistics,2004,32(2):407-499.
[43]
T Hesterberg,N H Choi,L Meier.Least angle and l1 penalized regression:A review [J].Statistics Surveys,2008,2:61-93.
[44]
R J Tibshirani,J Taylor.The solution path of the generalized lasso [J].The Annals of Statistics,2011,39(3):1335-1371.
[45]
Y Wang,Q Wu.Sparse PCA by iterative elimination algorithm [J].Advances in Computational Mathematics,2011,36(1):137-151.
[46]
I M Johnstone,A Y Lu.On consistency and sparsity for principal components analysis in high dimensions [J].Journal of the American Statistical Association,2009,104(486):682-693.
[47]
B Nadler.Discussion [J].Journal of the American Statistical Association,2009,104(486):694-697.
