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.

Getting started

Package details

AuthorRunze Li [aut], Wanghuan Chu [aut], Liying Huang [aut, cre], John Dziak [aut]
Date of publication2016-07-28 17:28:27
MaintainerLiying Huang <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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VariableScreening documentation built on May 30, 2017, 3:06 a.m.