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)).

Reference manual

install.packages("SIS")

1.5 by Yang Feng, 7 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] , Arce Domingo Relloso [aut]

Documentation: PDF Manual

GPL-2 license

Imports glmnet, ncvreg, survival, nnet, doParallel, gcdnet, msaenet, foreach, methods

Suggests rmarkdown, knitr, formatR, pROC

Linking to Rcpp, RcppEigen

Imported by RsqMed, crossurr, gfiUltra, hySAINT, misspi, multiModTest.

Suggested by SuperLearner, quadVAR, subsemble.

See at CRAN