Extremely fast algorithm "QICD", Iterative Coordinate Descent Algorithm for High-dimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate descent algorithm in the inner iteration with the majorization minimization step in the outside step. For each inner univariate minimization problem, we only need to compute a one-dimensional weighted median, which ensures fast computation. Tuning parameter selection is based on two different method: the cross validation and BIC for quantile regression model. Details are described in Peng,B and Wang,L. (2015) <doi:10.1080/10618600.2014.913516>.
| Version: | 1.2.0 |
| Depends: | R (≥ 3.0.0) |
| Imports: | stats, parallel |
| Suggests: | mvtnorm, knitr |
| Published: | 2017-04-18 |
| Author: | Bo Peng [aut, cre], Rondall E. Jones [ctb], John A. Wisniewski [ctb] |
| Maintainer: | Bo Peng <peng0199 at umn.edu> |
| License: | GPL-2 |
| URL: | http://www.tandfonline.com/doi/abs/10.1080/10618600.2014.913516#.VsoK-JMrJp8 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | QICD results |
| Reference manual: | QICD.pdf |
| Vignettes: |
vignette vignette |
| Package source: | QICD_1.2.0.tar.gz |
| Windows binaries: | r-devel: QICD_1.2.0.zip, r-release: QICD_1.2.0.zip, r-oldrel: QICD_1.2.0.zip |
| OS X El Capitan binaries: | r-release: QICD_1.2.0.tgz |
| OS X Mavericks binaries: | r-oldrel: QICD_1.2.0.tgz |
| Old sources: | QICD archive |
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