CRAN Package Check Results for Package GSparO (original) (raw)
Last updated on 2025-01-13 05:48:22 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0 | 4.24 | 39.86 | 44.10 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.0 | 3.66 | 29.81 | 33.47 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 1.0 | 70.92 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.0 | 66.81 | NOTE | |||
| r-devel-windows-x86_64 | 1.0 | 7.00 | 58.00 | 65.00 | NOTE | |
| r-patched-linux-x86_64 | 1.0 | 4.28 | 38.57 | 42.85 | NOTE | |
| r-release-linux-x86_64 | 1.0 | 4.09 | 38.22 | 42.31 | NOTE | |
| r-release-macos-arm64 | 1.0 | 25.00 | NOTE | |||
| r-release-macos-x86_64 | 1.0 | 47.00 | NOTE | |||
| r-release-windows-x86_64 | 1.0 | 6.00 | 55.00 | 61.00 | NOTE | |
| r-oldrel-macos-arm64 | 1.0 | 29.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 1.0 | 37.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 1.0 | 7.00 | 66.00 | 73.00 | NOTE |
Check Details
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
Version: 1.0
Check: LazyData
Result: NOTE 'LazyData' is specified without a 'data' directoryFlavors: 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