TY - JOUR AU - Meuwissen, T. H. E. AU - Hayes, B. J. AU - Goddard, M. E. PY - 2001 DA - 2001// TI - Prediction of total genetic value using genome-wide dense marker maps JO - Genetics VL - 157 ID - Meuwissen2001 ER - TY - JOUR AU - Kennard, R. W. PY - 1970 DA - 1970// TI - Ridge regression: biased estimation for non-orthogonal problems JO - Technometrics VL - 12 UR - https://doi.org/10.1080/00401706.1970.10488634 DO - 10.1080/00401706.1970.10488634 ID - Kennard1970 ER - TY - JOUR AU - Tibshirani, R. PY - 1996 DA - 1996// TI - Regression shrinkage and selection via the lasso JO - J Roy Statist Soc Ser B VL - 58 ID - Tibshirani1996 ER - TY - JOUR AU - Hastie, T. PY - 2005 DA - 2005// TI - Regularization and variable selection via the elastic net JO - J Roy Statist Soc Ser B VL - 67 UR - https://doi.org/10.1111/j.1467-9868.2005.00503.x DO - 10.1111/j.1467-9868.2005.00503.x ID - Hastie2005 ER - TY - JOUR AU - Frank, I. E. AU - Friedman, J. H. PY - 1993 DA - 1993// TI - A statistical view of some chemometrics regression tools (with discussion) JO - Technometrics VL - 35 UR - https://doi.org/10.1080/00401706.1993.10485033 DO - 10.1080/00401706.1993.10485033 ID - Frank1993 ER - TY - JOUR AU - Heslot, N. AU - Yang, H. P. AU - Sorrells, M. E. AU - Jannink, J. L. PY - 2012 DA - 2012// TI - Genomic selection in plant breeding: a comparison of models JO - Crop Sci VL - 52 UR - https://doi.org/10.2135/cropsci2011.06.0297 DO - 10.2135/cropsci2011.06.0297 ID - Heslot2012 ER - TY - STD TI - Ogutu JO, Schulz-Streeck T, Piepho H-P: Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions. BMC Proceedings. 2012, BioMed Central Ltd, 6 (Suppl 2): ID - ref7 ER - TY - JOUR AU - Huang, J. AU - Horowitz, J. L. AU - Ma, S. PY - 2008 DA - 2008// TI - Asymptotic properties of bridge estimators in sparse high-dimensional regression models JO - Ann Statist VL - 36 UR - https://doi.org/10.1214/009053607000000875 DO - 10.1214/009053607000000875 ID - Huang2008 ER - TY - JOUR AU - Fu, W. J. PY - 1998 DA - 1998// TI - Penalized regressions: The bridge versus the lasso JO - J Comput Graph Statist VL - 7 ID - Fu1998 ER - TY - JOUR AU - Knight, K. AU - Fu, W. PY - 2000 DA - 2000// TI - Asymptotics for Lasso-type estimators JO - Ann Statist VL - 28 ID - Knight2000 ER - TY - JOUR AU - Fan, J. AU - Li, R. PY - 2001 DA - 2001// TI - Variable selection via nonconcave penalized likelihood and its oracle Properties JO - J Amer Statist Assoc VL - 96 UR - https://doi.org/10.1198/016214501753382273 DO - 10.1198/016214501753382273 ID - Fan2001 ER - TY - JOUR AU - Fan, J. AU - Peng, H. PY - 2004 DA - 2004// TI - Nonconcave penalized likelihood with a diverging number of parameters JO - Ann Stat VL - 32 UR - https://doi.org/10.1214/009053604000000256 DO - 10.1214/009053604000000256 ID - Fan2004 ER - TY - JOUR AU - Whittaker, J. C. AU - Thompson, R. AU - Denham, M. C. PY - 2000 DA - 2000// TI - Marker-assisted selection using ridge regression JO - Genet Res VL - 75 UR - https://doi.org/10.1017/S0016672399004462 DO - 10.1017/S0016672399004462 ID - Whittaker2000 ER - TY - JOUR AU - Piepho, H. P. PY - 2009 DA - 2009// TI - Ridge regression and extensions for genomewide selection in maize JO - Crop Sci VL - 49 UR - https://doi.org/10.2135/cropsci2008.10.0595 DO - 10.2135/cropsci2008.10.0595 ID - Piepho2009 ER - TY - JOUR AU - Piepho, H. -. P. AU - Ogutu, J. O. AU - Schulz-Streeck, T. AU - Estaghvirou, B. AU - Gordillo, A. AU - Technow, F. PY - 2012 DA - 2012// TI - Efficient computation of ridge-regression best linear unbiased prediction in genomic selection in plant breeding JO - Crop Sci VL - 52 UR - https://doi.org/10.2135/cropsci2011.11.0592 DO - 10.2135/cropsci2011.11.0592 ID - Piepho2012 ER - TY - JOUR AU - Zhang, C. H. PY - 2010 DA - 2010// TI - Nearly unbiased variable selection under minimax concave penalty JO - Ann Stat VL - 38 UR - https://doi.org/10.1214/09-AOS729 DO - 10.1214/09-AOS729 ID - Zhang2010 ER - TY - CHAP AU - Zhang, C. H. PY - 2007 DA - 2007// BT - Penalized linear unbiased selection ID - Zhang2007 ER - TY - JOUR AU - Zhou, H. PY - 2006 DA - 2006// TI - The adaptive lasso and its oracle properties JO - J Amer Stat Assoc VL - 101 UR - https://doi.org/10.1198/016214506000000735 DO - 10.1198/016214506000000735 ID - Zhou2006 ER - TY - JOUR AU - Breheny, P. AU - Huang, J. PY - 2009 DA - 2009// TI - Penalized methods for bi-level variable selection JO - Stat Interface VL - 2 UR - https://doi.org/10.4310/SII.2009.v2.n3.a10 DO - 10.4310/SII.2009.v2.n3.a10 ID - Breheny2009 ER - TY - JOUR AU - Breheny, P. AU - Huang, J. PY - 2011 DA - 2011// TI - Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection JO - Ann Appl Stat VL - 5 UR - https://doi.org/10.1214/10-AOAS388 DO - 10.1214/10-AOAS388 ID - Breheny2011 ER - TY - JOUR AU - Huang, J. AU - Breheny, P. AU - Ma, S. PY - 2012 DA - 2012// TI - A selective review of group selection in high-dimensional models JO - Statist Sci VL - 27 UR - https://doi.org/10.1214/12-STS392 DO - 10.1214/12-STS392 ID - Huang2012 ER - TY - JOUR AU - Huang, J. AU - Ma, S. AU - Xie, H. AU - Zhang, C. H. PY - 2009 DA - 2009// TI - A group bridge approach for variable selection JO - Biometrika VL - 96 UR - https://doi.org/10.1093/biomet/asp020 DO - 10.1093/biomet/asp020 ID - Huang2009 ER - TY - JOUR AU - Park, C. AU - Yoon, Y. J. PY - 2011 DA - 2011// TI - Bridge regression: adaptivity and group selection JO - J Statist Plann Inference VL - 141 UR - https://doi.org/10.1016/j.jspi.2011.05.004 DO - 10.1016/j.jspi.2011.05.004 ID - Park2011 ER - TY - JOUR AU - Yuan, M. AU - Lin, Y. PY - 2006 DA - 2006// TI - Model selection and estimation in regression with grouped variables JO - J Roy Statist Soc Ser B VL - 68 UR - https://doi.org/10.1111/j.1467-9868.2005.00532.x DO - 10.1111/j.1467-9868.2005.00532.x ID - Yuan2006 ER - TY - JOUR AU - Simon, N. AU - Friedman, J. AU - Hastie, T. AU - Tibshirani, R. PY - 2013 DA - 2013// TI - A sparse-group lasso JO - J Comput Graph Statist VL - 22 UR - https://doi.org/10.1080/10618600.2012.681250 DO - 10.1080/10618600.2012.681250 ID - Simon2013 ER - TY - JOUR AU - Nardi, Y. AU - Rinaldo, A. PY - 2008 DA - 2008// TI - On the asymptotic properties of the group lasso estimator for linear models JO - Electron J Statist VL - 2 UR - https://doi.org/10.1214/08-EJS200 DO - 10.1214/08-EJS200 ID - Nardi2008 ER - TY - JOUR AU - Wang, H. AU - Leng, C. PY - 2008 DA - 2008// TI - A note on adaptive group lasso JO - Comput Statist Appl Data Anal VL - 52 UR - https://doi.org/10.1016/j.csda.2008.05.006 DO - 10.1016/j.csda.2008.05.006 ID - Wang2008 ER - TY - JOUR AU - Zhang, C. -. H. AU - Huang, J. PY - 2008 DA - 2008// TI - The sparsity and bias of the lasso selection in high-dimensional linear regression JO - Ann Stat VL - 36 UR - https://doi.org/10.1214/07-AOS520 DO - 10.1214/07-AOS520 ID - Zhang2008 ER - TY - JOUR AU - Peng, J. AU - Zhu, J. AU - Bergamaschi, A. AU - Han, W. AU - Noh, D. Y. AU - Pollack, J. R. AU - Wang, P. PY - 2010 DA - 2010// TI - Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer JO - Ann Appl Stat VL - 4 UR - https://doi.org/10.1214/09-AOAS271 DO - 10.1214/09-AOAS271 ID - Peng2010 ER - TY - CHAP AU - Friedman, J. AU - Hastie, T. AU - Tibshirani, R. PY - 2010 DA - 2010// BT - A note on the group lasso and sparse group lasso ID - Friedman2010 ER - TY - CHAP AU - Friedman, J. AU - Hastie, T. AU - Tibshirani, R. PY - 2008 DA - 2008// BT - Regularization paths for generalized linear models via coordinate descent ID - Friedman2008 ER - TY - JOUR AU - Yang, Y. PY - 2005 DA - 2005// TI - Can the strengths of AIC and BIC be shared? JO - Biometrika VL - 92 UR - https://doi.org/10.1093/biomet/92.4.937 DO - 10.1093/biomet/92.4.937 ID - Yang2005 ER - TY - JOUR AU - Martinez, J. G. AU - Carroll, R. J. AU - Müller, S. AU - Sampson, J. N. AU - Chartterjee, N. PY - 2011 DA - 2011// TI - Empirical performance of cross-validation with oracle methods in genomic context JO - Amer Statist VL - 65 UR - https://doi.org/10.1198/tas.2011.11052 DO - 10.1198/tas.2011.11052 ID - Martinez2011 ER - TY - STD TI - Jacob L, Obozinski G, Vert J-P: Group lasso with overlap and graph lasso. Proceedings of the 26th annual international conference on machine learning. Montreal, Canada. ICML 2009, 433-440. ACM, New York, NY, USA ID - ref34 ER - TY - CHAP AU - Percival, D. PY - 2011 DA - 2011// TI - Theoretical properties of the overlapping groups lasso BT - Electron J Stat ID - Percival2011 ER - TY - JOUR AU - Zhao, P. AU - Rocha, G. AU - Yu, B. PY - 2009 DA - 2009// TI - The composite absolute penalties family for grouped and hierarchical variable selection JO - Ann Stat VL - 37 UR - https://doi.org/10.1214/07-AOS584 DO - 10.1214/07-AOS584 ID - Zhao2009 ER - TY - JOUR AU - Bien, J. AU - Taylor, J. AU - Tibshirani, R. PY - 2013 DA - 2013// TI - A lasso for hierarchical interactions JO - Ann Stat VL - 41 UR - https://doi.org/10.1214/13-AOS1096 DO - 10.1214/13-AOS1096 ID - Bien2013 ER - TY - STD TI - Lim M, Hastie T: Learning interactions through hierarchical group-lasso regularization. [http://arxiv.org/pdf/1308.2719v1.pdf] UR - http://arxiv.org/pdf/1308.2719v1.pdf ID - ref38 ER - TY - JOUR AU - Meier, L. AU - van der Geer, S. AU - Bühlmann, P. PY - 2008 DA - 2008// TI - The group lasso for logistic regression JO - J Roy Statist Soc Ser B VL - 70 UR - https://doi.org/10.1111/j.1467-9868.2007.00627.x DO - 10.1111/j.1467-9868.2007.00627.x ID - Meier2008 ER - TY - CHAP AU - Roth, V. AU - Fischer, B. PY - 2009 DA - 2009// TI - The group-lasso for generalized linear models: uniqueness of solutions and efficient algorithms BT - Proceedings of the 25th annual international conference on machine learning PB - ICML CY - Helsinski, Finland ID - Roth2009 ER - TY - JOUR AU - Bach, F. PY - 2008 DA - 2008// TI - Consistency of the group lasso and multiple kernel learning JO - J Mach Learn VL - 9 ID - Bach2008 ER -