Last updated on 2025-10-30 17:50:01 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags | 
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0 | 4.40 | 54.26 | 58.66 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.0 | 3.73 | 39.14 | 42.87 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 1.0 | 11.00 | 81.33 | 92.33 | NOTE | |
| r-devel-linux-x86_64-fedora-gcc | 1.0 | 10.00 | 76.69 | 86.69 | NOTE | |
| r-devel-windows-x86_64 | 1.0 | 6.00 | 65.00 | 71.00 | NOTE | |
| r-patched-linux-x86_64 | 1.0 | 4.88 | 51.22 | 56.10 | NOTE | |
| r-release-linux-x86_64 | 1.0 | 5.18 | 52.59 | 57.77 | NOTE | |
| r-release-macos-arm64 | 1.0 | 3.00 | 26.00 | 29.00 | NOTE | |
| r-release-macos-x86_64 | 1.0 | 4.00 | 43.00 | 47.00 | NOTE | |
| r-release-windows-x86_64 | 1.0 | 7.00 | 66.00 | 73.00 | NOTE | |
| r-oldrel-macos-arm64 | 1.0 | 2.00 | 23.00 | 25.00 | NOTE | |
| r-oldrel-macos-x86_64 | 1.0 | 5.00 | 42.00 | 47.00 | NOTE | |
| r-oldrel-windows-x86_64 | 1.0 | 9.00 | 80.00 | 89.00 | NOTE | 
Version: 1.0
Check: Rd files
Result: NOTE
  checkRd: (-1) GSparO.Rd:23: Lost braces; missing escapes or markup?
      23 | Group sparse optimization (GSparO) for least squares regression by using the proximal gradient algorithm to solve the L_{2,1/2} regularization model.
         |                                                                                                                         ^
  checkRd: (-1) GSparO.Rd:26: Lost braces; missing escapes or markup?
      26 | GSparO is group sparse optimization for least squares regression described in [Hu et al(2017)], in which the proximal gradient algorithm is implemented to solve the L_{2,1/2} regularization model. GSparO is an iterative algorithm consisting of a gradient step for the least squares regression and a proximal steps for the L_{2,1/2} penalty, which is analytically formulated in this function. Also, GSparO can solve sparse variable selection problem in absence of group structure. In particular, setting group in GSparO be a vector of ones, GSparO is reduced to the iterative half thresholding algorithm introduced in [Xu et al (2012)].
         |                                                                                                                                                                        ^
  checkRd: (-1) GSparO.Rd:26: Lost braces; missing escapes or markup?
      26 | GSparO is group sparse optimization for least squares regression described in [Hu et al(2017)], in which the proximal gradient algorithm is implemented to solve the L_{2,1/2} regularization model. GSparO is an iterative algorithm consisting of a gradient step for the least squares regression and a proximal steps for the L_{2,1/2} penalty, which is analytically formulated in this function. Also, GSparO can solve sparse variable selection problem in absence of group structure. In particular, setting group in GSparO be a vector of ones, GSparO is reduced to the iterative half thresholding algorithm introduced in [Xu et al (2012)].
         |                                                                                                                                                                                                                                                                                                                                     ^
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.0
Check: LazyData
Result: NOTE
    'LazyData' is specified without a 'data' directory
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64