VariableScreening: High-Dimensional Screening for Semiparametric Longitudinal Regression
Version 0.1.1

Implements a screening procedure proposed by Wanghuan Chu, Runze Li and Matthew Reimherr (2016) 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.

AuthorRunze Li [aut], Wanghuan Chu [aut], Liying Huang [aut, cre], John Dziak [aut]
Date of publication2016-07-28 17:28:27
MaintainerLiying Huang <lxh37@PSU.EDU>
LicenseGPL (>= 2)
Version0.1.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("VariableScreening")

Popular man pages

simulateLD: Simulate a dataset for testing the performance of screenlong
screenlong: Perform high-dimensional screening for semiparametric...
See all...

All man pages Function index File listing

Man pages

screenlong: Perform high-dimensional screening for semiparametric...
simulateLD: Simulate a dataset for testing the performance of screenlong

Functions

screenlong Man page Source code
simulateLD Man page Source code

Files

NAMESPACE
R
R/simulateLD.R
R/screenlong.R
MD5
DESCRIPTION
man
man/screenlong.Rd
man/simulateLD.Rd
VariableScreening documentation built on May 20, 2017, 12:55 a.m.

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