Correlated variables in regression: Clustering and sparse estimation
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[1] Peter Bühlmann,et al. High-Dimensional Statistics with a View Toward Applications in Biology , 2014 .
[2] Noah Simon,et al. A Sparse-Group Lasso , 2013 .
[3] S. Geer,et al. The Lasso, correlated design, and improved oracle inequalities , 2011, 1107.0189.
[4] Jian Huang,et al. The Sparse Laplacian Shrinkage Estimator for High-Dimensional Regression. , 2011, Annals of statistics.
[5] Thomas Lengauer,et al. Classification with correlated features: unreliability of feature ranking and solutions , 2011, Bioinform..
[6] Sara van de Geer,et al. Statistics for High-Dimensional Data: Methods, Theory and Applications , 2011 .
[7] Cun-Hui Zhang,et al. Scaled sparse linear regression , 2011, 1104.4595.
[8] Trevor Hastie,et al. Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.
[9] R. Tibshirani,et al. A note on the group lasso and a sparse group lasso , 2010, 1001.0736.
[10] S. Geer,et al. On the conditions used to prove oracle results for the Lasso , 2009, 0910.0722.
[11] S. Geer,et al. High-dimensional additive modeling , 2008, 0806.4115.
[12] N. Meinshausen,et al. LASSO-TYPE RECOVERY OF SPARSE REPRESENTATIONS FOR HIGH-DIMENSIONAL DATA , 2008, 0806.0145.
[13] P. Bickel,et al. SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR , 2008, 0801.1095.
[14] H. Zou,et al. One-step Sparse Estimates in Nonconcave Penalized Likelihood Models. , 2008, Annals of statistics.
[15] Cun-Hui Zhang,et al. The sparsity and bias of the Lasso selection in high-dimensional linear regression , 2008, 0808.0967.
[16] H. Bondell,et al. Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR , 2008, Biometrics.
[17] Y. She. Sparse regression with exact clustering , 2008 .
[18] Nicolai Meinshausen,et al. Relaxed Lasso , 2007, Comput. Stat. Data Anal..
[19] H. Zou. The Adaptive Lasso and Its Oracle Properties , 2006 .
[20] Peng Zhao,et al. On Model Selection Consistency of Lasso , 2006, J. Mach. Learn. Res..
[21] D. Balding. A tutorial on statistical methods for population association studies , 2006, Nature Reviews Genetics.
[22] N. Meinshausen,et al. High-dimensional graphs and variable selection with the Lasso , 2006, math/0608017.
[23] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .
[24] H. Bondell,et al. Simultaneous regression shrinkage , variable selection and clustering of predictors with OSCAR , 2006 .
[25] H. Zou,et al. Regularization and variable selection via the elastic net , 2005 .
[26] R. Shibata,et al. PARTIAL CORRELATION AND CONDITIONAL CORRELATION AS MEASURES OF CONDITIONAL INDEPENDENCE , 2004 .
[27] Peter Bühlmann,et al. Finding predictive gene groups from microarray data , 2004 .
[28] C. Carlson,et al. Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. , 2004, American journal of human genetics.
[29] Anja Vogler,et al. An Introduction to Multivariate Statistical Analysis , 2004 .
[30] Kam D. Dahlquist,et al. Regression Approaches for Microarray Data Analysis , 2002, J. Comput. Biol..
[31] S. Szarek,et al. Chapter 8 - Local Operator Theory, Random Matrices and Banach Spaces , 2001 .
[32] R. Tibshirani,et al. Supervised harvesting of expression trees , 2001, Genome Biology.
[33] Ash A. Alizadeh,et al. 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns , 2000, Genome Biology.
[34] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[35] Maurice G. Kendall,et al. A course in multivariate analysis , 1958 .