FanJianqingLiRunze. 2001. “Variable Selection via Nonconcave Penalized Likelihood and Its Oracle Properties.” Journal of the American Statistical Association96(456):1348–60.
3.
FanJianqingLvJinchi. 2008. “Sure Independence Screening for Ultrahigh Dimensional Feature Space.” Journal of the Royal Statistical Society, Series B (Statistical Methodology)70(5):849–911.
4.
GhoshSamiran. 2011. “On the Grouped Selection and Model Complexity of the Adaptive Elastic Net.” Statistics and Computing21(3):451–62.
5.
HainmuellerJensHazlettChad. 2012. “Kernel Regularized Least Squares: Moving beyond Linearity and Additivity without Sacrificing Interpretability.” Retrieved June 20, 2014 (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2046206).
6.
HastieTrevorTibshiraniRobertFriedmanJerome. 2009. The Elements of Statistical Learning: Data Mining, Inference and Prediction. 2nd ed.New York: Springer.
7.
JamesGarethWittenDanielaHastieTrevorTibshiraniRobert. 2013. An Introduction to Statistical Learning. New York: Springer.
8.
RihouxBenoitRaginCharles C.2008. Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques. Thousand Oaks, CA: Sage.
9.
RinaldoAlessandro. 2009. “Properties and Refinements of the Fused Lasso.” Annals of Statistics37(5B):2922–52.
10.
TibshiraniRobert. 1996. “Regression Shrinkage and Selection via the Lasso: A Retrospective.” Journal of the Royal Statistical Society, Series B (Methodological)73(3):267-88.
11.
WangHanshengLengChenlei. 2008. “A Note on Adaptive Group Lasso.” Computational Statistics and Data Analysis52(12):5277–86.
12.
ZouHui. 2006. “The Adaptive Lasso and Its Oracle Properties.” Journal of the American Statistical Association101(476):1418–29.
13.
ZouHuiHastieTrevor. 2003. “Regression Shrinkage and Selection via the Elastic Net, with Applications to Microarrays.” Journal of the Royal Statistical Society, Series B67:301–20.