SIS

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.

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Description file content

Package
SIS
Version
0.8-6
Date
2018-02-13
Title
Sure Independence Screening
Author
Jianqing Fan, Yang Feng, Diego Franco Saldana, Richard Samworth, Yichao Wu
Maintainer
Yang Feng
Depends
R (>= 3.2.4)
Imports
glmnet, ncvreg, survival
Description
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.
License
GPL-2
RoxygenNote
6.0.1
NeedsCompilation
no
Packaged
2018-02-13 07:24:38 UTC; yangfeng
Repository
CRAN
Date/Publication
2018-02-13 23:52:33 UTC

install.packages('SIS')

0.8-6

5 days ago

Yang Feng

GPL-2

Depends on

R (>= 3.2.4)

Imports

glmnet, ncvreg, survival

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