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) , Runze LI, Wei ZHONG, & Liping ZHU (2012) , Jingyuan LIU, Runze LI, & Rongling WU (2014) Hengjian CUI, Runze LI, & Wei ZHONG (2015) , and Wanghuan CHU, Runze LI and Matthew REIMHERR (2016) . 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.


Reference manual

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0.2.0 by Liying Huang, 3 years ago

Browse source code at https://github.com/cran/VariableScreening

Authors: Runze Li [aut] , Liying Huang [aut, cre] , John Dziak [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports gee, expm, splines, MASS, energy

See at CRAN