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SIS
View on CRAN: Click
here
Download and install SIS package within the R console
Install from CRAN:
install.packages("SIS")
Install from Github:
library("remotes")
install_github("cran/SIS")
Install by package version:
library("remotes")
install_version("SIS", "0.8-8")
Attach the package and use:
library("SIS")
Maintained by
Yang Feng
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2009-08-14
Latest Update: 2020-01-27
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) (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>).
How to cite:
Yang Feng (2009). SIS: Sure Independence Screening. R package version 0.8-8, https://cran.r-project.org/web/packages/SIS. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1 (2009-08-14 22:24), 0.2 (2009-08-19 10:14), 0.3 (2009-12-09 09:52), 0.4 (2010-04-21 15:15), 0.5 (2010-07-09 10:43), 0.6 (2010-09-06 20:12), 0.7-1 (2014-04-20 07:43), 0.7-2 (2014-05-06 07:04), 0.7-3 (2014-07-23 00:34), 0.7-4 (2014-08-01 07:55), 0.7-5 (2015-03-16 19:27), 0.7-6 (2015-11-06 05:49), 0.7 (2014-04-16 00:28), 0.8-1 (2016-08-13 23:48), 0.8-3 (2016-10-12 09:00), 0.8-4 (2017-04-21 20:48), 0.8-6 (2018-02-14 00:52), 0.8-7 (2019-11-20 09:50)
Other packages that cited SIS R package
View SIS citation profile
Other R packages that SIS depends,
imports, suggests or enhances
Complete documentation for SIS
Functions, R codes and Examples using
the SIS R package
Some associated functions: SIS . leukemia.test . leukemia.train . predict.SIS . prostate.test . prostate.train . standardize . tune.fit .
Some associated R codes: SIS.R . predict.SIS.R . standardize.R . subfuns.R . tune.fit.R . Full SIS package functions and examples
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