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.

Getting started

Package details

AuthorRunze Li [aut], Liying Huang [aut, cre], John Dziak [aut]
MaintainerLiying Huang <[email protected]>
LicenseGPL (>= 2)
Version0.2.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("VariableScreening")

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VariableScreening documentation built on May 2, 2019, 6:54 a.m.