VariableScreening: High-Dimensional Screening for Semiparametric Longitudinal
Regression
Implements variable screening techniques for ultra-high
dimensional regression settings. Techniques for independent (iid) data,
varying-coefficient models, and longitudinal data are implemented. The package
currently contains three screen functions: screenIID(), screenLD() and screenVCM(),
and six methods for simulating dataset: simulateDCSIS(), simulateLD, simulateMVSIS(),
simulateMVSISNY(), simulateSIRS() and simulateVCM(). The package is based on the work of
Li-Ping ZHU, Lexin LI, Runze LI, and Li-Xing ZHU (2011) <doi:10.1198/jasa.2011.tm10563>,
Runze LI, Wei ZHONG, & Liping ZHU (2012) <doi:10.1080/01621459.2012.695654>,
Jingyuan LIU, Runze LI, & Rongling WU (2014) <doi:10.1080/01621459.2013.850086>
Hengjian CUI, Runze LI, & Wei ZHONG (2015) <doi:10.1080/01621459.2014.920256>, and
Wanghuan CHU, Runze LI and Matthew REIMHERR (2016) <doi:10.1214/16-AOAS912>.
Version: |
0.2.1 |
Depends: |
R (≥ 3.2.1) |
Imports: |
gee, expm, splines, MASS, energy |
Published: |
2022-06-23 |
Author: |
Runze Li [aut],
Liying Huang [aut],
John Dziak [aut, cre] |
Maintainer: |
John Dziak <dziakj1 at gmail.com> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
Copyright: |
(c) 2022 by Runze LI |
NeedsCompilation: |
no |
CRAN checks: |
VariableScreening results |
Documentation:
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