VariableScreening: High-Dimensional Screening for Semiparametric Longitudinal Regression
Implements a screening procedure proposed by Wanghuan Chu, Runze Li and Matthew Reimherr (2016) <DOI:10.1214/16-AOAS912> 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.
- Runze Li [aut], Wanghuan Chu [aut], Liying Huang [aut, cre], John Dziak [aut]
- Date of publication
- 2016-07-28 17:28:27
- Liying Huang <lxh37@PSU.EDU>
- GPL (>= 2)
- Perform high-dimensional screening for semiparametric...
- Simulate a dataset for testing the performance of screenlong
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