SIS (0.8-6)

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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) and all of its variants in generalized linear models and the Cox proportional hazards model.

Maintainer: Yang Feng
Author(s): Jianqing Fan, Yang Feng, Diego Franco Saldana, Richard Samworth, Yichao Wu

License: GPL-2

Uses: glmnet, ncvreg, survival
Reverse depends: SparseLearner
Reverse suggests: SuperLearner

Released almost 2 years ago.

16 previous versions



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