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>. Special thanks are due to Ling Zhang for providing detailed testing and proposing a method for speed improvement on the simulation of data with AR-1 structure.

Version: 0.2.0
Depends: R (≥ 3.2.1)
Imports: gee, expm, splines, MASS, energy
Published: 2018-08-09
Author: Runze Li [aut], Liying Huang [aut, cre], John Dziak [aut]
Maintainer: Liying Huang <lxh37 at PSU.EDU>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: The Pennsylvania State University
NeedsCompilation: no
CRAN checks: VariableScreening results


Reference manual: VariableScreening.pdf
Package source: VariableScreening_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: VariableScreening_0.2.0.tgz, r-oldrel: VariableScreening_0.2.0.tgz
Old sources: VariableScreening archive


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