High-Dimensional Screening for Semiparametric Longitudinal Regression R package VariableScreening version 0.2.1 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>. Software Depends: R (>= 3.2.1) Imports: gee, expm, splines, MASS, energy John Dziak <dziakj1@gmail.com> Comprehensive R Archive Network (CRAN) Runze Li [aut], Liying Huang [aut], John Dziak [aut, cre] GPL (>= 2) 2022-06-23 application/tgz https://CRAN.R-project.org/package=VariableScreening doi:10.32614/CRAN.package.VariableScreening