SIS

Variable selection techniques are essential tools for model selection and estimation in high-dimensional statistical models. Through this publicly available package, we provide a unified environment to carry out variable selection using iterative sure independence screening (SIS) (Fan and Lv (2008)doi:10.1111/j.1467-9868.2008.00674.x) and all of its variants in generalized linear models (Fan and Song (2009)doi:10.1214/10-AOS798) and the Cox proportional hazards model (Fan, Feng and Wu (2010)doi:10.1214/10-IMSCOLL606).