Description
Efficient implementations for Sorted L-One Penalized Estimation (SLOPE): generalized linear models regularized with the sorted L1-norm (Bogdan et al. 2015). Supported models include ordinary least-squares regression, binomial regression, multinomial regression, and Poisson regression. Both dense and sparse predictor matrices are supported. In addition, the package features predictor screening rules that enable fast and efficient solutions to high-dimensional problems.
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Show all 14 flavors
| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-macos-arm64 | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | NOTE |
| r-oldrel-macos-x86_64 | NOTE |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Check details (14 non-OK)
OK
r-devel-linux-x86_64-debian-clang
*
OK
r-devel-linux-x86_64-debian-gcc
*
OK
r-devel-linux-x86_64-fedora-clang
*
OK
r-devel-linux-x86_64-fedora-gcc
*
OK
r-devel-macos-arm64
*
OK
r-devel-windows-x86_64
*
NOTE
r-oldrel-macos-arm64
installed package size
installed size is 36.0Mb
sub-directories of 1Mb or more:
libs 34.8Mb
NOTE
r-oldrel-macos-x86_64
installed package size
installed size is 37.3Mb
sub-directories of 1Mb or more:
libs 36.1Mb
OK
r-oldrel-windows-x86_64
*
OK
r-patched-linux-x86_64
*
OK
r-release-linux-x86_64
*
OK
r-release-macos-arm64
*
OK
r-release-macos-x86_64
*
OK
r-release-windows-x86_64
*
Check History
NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE
r-oldrel-macos-arm64
installed package size
installed size is 36.0Mb
sub-directories of 1Mb or more:
libs 34.8Mb
NOTE
r-oldrel-macos-x86_64
installed package size
installed size is 37.3Mb
sub-directories of 1Mb or more:
libs 36.1Mb
Reverse Dependencies (1)
imports
Dependency Network
Version History
new
2.0.0
Mar 9, 2026