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.
Go to the COSSO Page for more details.
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(external link) and the instruction file(external link) (updated on March 2009) here. Run "example.m".
scadsvm.m was recently updated. Please replace the old version with the new code(external link)
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.(external link)