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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>).
| Version: | 0.8-8 |
| Depends: | R (≥ 3.2.4) |
| Imports: | glmnet, ncvreg, survival |
| Published: | 2020-01-27 |
| Author: | Yang Feng [aut, cre], Jianqing Fan [aut], Diego Franco Saldana [aut], Yichao Wu [aut], Richard Samworth [aut] |
| Maintainer: | Yang Feng <yangfengstat at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | SIS citation info |
| In views: | MachineLearning |
| CRAN checks: | SIS results |
| Reference manual: | SIS.pdf |
| Package source: | SIS_0.8-8.tar.gz |
| Windows binaries: | r-devel: SIS_0.8-8.zip, r-release: SIS_0.8-8.zip, r-oldrel: SIS_0.8-8.zip |
| macOS binaries: | r-release (arm64): SIS_0.8-8.tgz, r-oldrel (arm64): SIS_0.8-8.tgz, r-release (x86_64): SIS_0.8-8.tgz, r-oldrel (x86_64): SIS_0.8-8.tgz |
| Old sources: | SIS archive |
| Reverse imports: | crossurr, gfiUltra, hySAINT, misspi, RsqMed, SILM |
| Reverse suggests: | MFSIS, subsemble, SuperLearner |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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