Package: VariableScreening 0.2.1

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>.

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

VariableScreening_0.2.1.tar.gz
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VariableScreening_0.2.1.tgz(r-4.4-any)VariableScreening_0.2.1.tgz(r-4.3-any)
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VariableScreening.pdf |VariableScreening.html✨
VariableScreening/json (API)

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9 exports 1 stars 0.91 score 9 dependencies 2 dependents 11 scripts 280 downloads

Last updated 2 years agofrom:e8fdd4fc42. Checks:OK: 3 NOTE: 4. Indexed: yes.

Exports:screenIIDscreenLDscreenVCMsimulateDCSISsimulateLDsimulateMVSISsimulateMVSISNYsimulateSIRSsimulateVCM

Dependencies:bootenergyexpmgeegsllatticeMASSMatrixRcpp