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)[https://doi.org/10.1111%2Fj.1467-9868.2008.00674.x]) and all of its variants in generalized linear models (Fan and Song (2009)[https://doi.org/10.1214%2F10-AOS798]) and the Cox proportional hazards model (Fan, Feng and Wu (2010)[https://doi.org/10.1214%2F10-IMSCOLL606]).

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