VariableScreening: High-Dimensional Screening for Semiparametric Longitudinal Regression

Implements a screening procedure proposed by Wanghuan Chu, Runze Li and Matthew Reimherr (2016) <doi:10.1214/16-AOAS912> for varying coefficient longitudinal models with ultra-high dimensional predictors . The effect of each predictor is allowed to vary over time, approximated by a low-dimensional B-spline. Within-subject correlation is handled using a generalized estimation equation approach with structure specified by the user. Variance is allowed to change over time, also approximated by a B-spline.

Version: 0.1.1
Depends: R (≥ 3.2.1)
Imports: gee, expm, splines, MASS
Published: 2016-07-28
Author: Runze Li [aut], Wanghuan Chu [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

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Reference manual: VariableScreening.pdf
Package source: VariableScreening_0.1.1.tar.gz
Windows binaries: r-devel: VariableScreening_0.1.1.zip, r-release: VariableScreening_0.1.1.zip, r-oldrel: VariableScreening_0.1.1.zip
OS X Mavericks binaries: r-release: VariableScreening_0.1.1.tgz, r-oldrel: VariableScreening_0.1.1.tgz
Old sources: VariableScreening archive

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