Sure Independence Screening

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)) and all of its variants in generalized linear models (Fan and Song (2009)) and the Cox proportional hazards model (Fan, Feng and Wu (2010)).


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Reference manual

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install.packages("SIS")

0.8-8 by Yang Feng, 10 months ago


Browse source code at https://github.com/cran/SIS


Authors: Yang Feng [aut, cre] , Jianqing Fan [aut] , Diego Franco Saldana [aut] , Yichao Wu [aut] , Richard Samworth [aut]


Documentation:   PDF Manual  


Task views: Machine Learning & Statistical Learning


GPL-2 license


Imports glmnet, ncvreg, survival


Imported by RsqMed, SILM.

Suggested by SuperLearner.


See at CRAN