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Extremely efficient procedures for fitting regularization path with l0, l1, and truncated lasso penalty for linear regression and logistic regression models. This version is a completely new version compared with our previous version, which was mainly based on R. New core algorithms are developed and are now written in C++ and highly optimized.
| Version: | 2.0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | foreach, doParallel, ggplot2 |
| Suggests: | rmarkdown, knitr, testthat (≥ 3.0.0) |
| Published: | 2021-12-17 |
| Author: | Chunlin Li [aut], Yu Yang [aut, cre], Chong Wu [aut] |
| Maintainer: | Yu Yang <yang6367 at umn.edu> |
| License: | GPL-3 |
| URL: | https://yuyangyy.com/glmtlp/ |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | glmtlp results |
| Reference manual: | glmtlp.pdf |
| Vignettes: |
glmtlp |
| Package source: | glmtlp_2.0.1.tar.gz |
| Windows binaries: | r-devel: glmtlp_2.0.1.zip, r-release: glmtlp_2.0.1.zip, r-oldrel: glmtlp_2.0.1.zip |
| macOS binaries: | r-release (arm64): glmtlp_2.0.1.tgz, r-oldrel (arm64): glmtlp_2.0.1.tgz, r-release (x86_64): glmtlp_2.0.1.tgz, r-oldrel (x86_64): glmtlp_2.0.1.tgz |
| Old sources: | glmtlp archive |
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These binaries (installable software) and packages are in development.
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