COSSO PAGE

COSSO: Component Selection and Smoothing for Multivariate Nonparametric Regression The software, written in the MATLAB language, conducts model selection and model fitting simultaneously in multivariate regression models. The nonparametric estimate is given by the framework of smoothing spline ANOVA models. The algorithm iteratively solves smoothing splines and the nonnegative garotte estimate. Written by Yi Lin and Hao Helen Zhang. The original paper is to appear at Annals of Statistics. Download the MATLAB code here.

COSSO in R The software implements the COSSO estimator in the R language. The following is the first version cosso_0.1.1. Written by Hao Helen Zhang and Yi Lin. Download the R code, the README file, and the documentation file here.

SCAD-SVM: Gene Selection for microarray data via SVM with nonconcave SCAD penalty A method of identifying important genes and classifying samples simultaneously for microarray gene expression data.  . MATLAB code was written by Hao Helen Zhang, Jeongyoun Ahn, Cheolwoo Park, and Xiaodong Lin. The original paper appeared in Bioinformatics. Download MATLAB code and the instruction file here. Run "example.m".

ALASSO-COX: Adaptive LASSO for Cox's Proportional Hazards Model A method of identifying significant risk factors using the penalized partial likelihood method with the weighted L1 penalty. . R code was written by Wenbin Lu and Hao Helen Zhang based on Wenjin Fu's shooting algorithm. The original paper will appear in Biometrika. Download the R code.