Title: LASSO and (adaptive) Elastic-Net penalized least squares,
logistic regression, HHSVM and squared hinge loss SVM using a

Title: LASSO and Elastic Net (Adaptive) Penalized Least Squares,
Logistic Regression, HHSVM, Squared Hinge SVM and Expectile
Description: A generalized coordinate descent (GCD) algorithm for computing the solution path of the hybrid Huberized support vector machine (HHSVM) and its generalization, including the LASSO and elastic net (adaptive) penalized least squares, logistic regression, HHSVM, squared hinge loss SVM and expectile regression.

Title: The (Adaptive) LASSO and Elastic Net Penalized Least Squares,
Logistic Regression, Hybrid Huberized Support Vector Machines,
Squared Hinge Loss Support Vector Machines and Expectile
Regression using a Fast Generalized Coordinate Descent
Author: Yi Yang <yi.yang6@mcgill.ca>, Yuwen Gu <yuwen.gu@uconn.edu>, Hui Zou
Description: Implements a generalized coordinate descent (GCD) algorithm
for computing the solution paths of the hybrid Huberized support vector
machine (HHSVM) and its generalizations. Supported models include the
(adaptive) LASSO and elastic net penalized least squares, logistic
regression, HHSVM, squared hinge loss SVM and expectile regression.

Title: Generalized Competing Event Model
Author: Hanjie Shen <has072@ucsd.edu>, Ruben Carmona
Description: Generalized competing event model based on Cox PH model and Fine-Gray model.
This function is designed to develop optimized risk-stratification methods for competing
1. Carmona R, Gulaya S, Murphy JD, Rose BS, Wu J, Noticewala S,McHale MT, Yashar CM, Vaida F,
and Mell LK.(2014) Validated competing event model for thestage I-II endometrial cancer
population. Int J Radiat Oncol Biol Phys.89:888-98. <DOI:10.1016/j.ijrobp.2014.03.047>.
2. Carmona R, Zakeri K, Green G, Hwang L, Gulaya S, Xu B, Verma R, Williamson CW, Triplett DP, Rose
BS, Shen H, Vaida F, Murphy JD, and Mell LK. (2016) Improved method to stratify elderly
cancer patients at risk for competing events. J Clin Oncol.in press. <DOI:10.1200/JCO.2015.65.0739>.