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To provide a comprehensive analysis of high dimensional longitudinal data,this package provides analysis for any combination of 1) simultaneous variable selection and estimation, 2) mean regression or quantile regression for heterogeneous data, 3) cross-sectional or longitudinal data, 4) balanced or imbalanced data, 5) moderate, high or even ultra-high dimensional data, via computationally efficient implementations of penalized generalized estimating equations.
| Version: | 0.2.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | mvtnorm, quantreg, Rcpp (≥ 0.10.2), doParallel, foreach |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | methods |
| Published: | 2024-11-12 |
| DOI: | 10.32614/CRAN.package.geeVerse |
| Author: | Tianhai Zu [aut, cre], Brittany Green [aut, ctb], Yan Yu [aut, ctb] |
| Maintainer: | Tianhai Zu <zuti at mail.uc.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | geeVerse results |
| Reference manual: | geeVerse.pdf |
| Package source: | geeVerse_0.2.2.tar.gz |
| Windows binaries: | r-devel: geeVerse_0.2.2.zip, r-release: geeVerse_0.2.2.zip, r-oldrel: geeVerse_0.2.2.zip |
| macOS binaries: | r-release (arm64): geeVerse_0.2.2.tgz, r-oldrel (arm64): geeVerse_0.2.2.tgz, r-release (x86_64): geeVerse_0.2.2.tgz, r-oldrel (x86_64): geeVerse_0.2.2.tgz |
| Old sources: | geeVerse archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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