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Minimize a differentiable function subject to all the variables being non-negative (i.e. >= 0), using a Conjugate-Gradient algorithm based on a modified Polak-Ribiere-Polyak formula as described in (Li, Can, 2013, <https://www.hindawi.com/journals/jam/2013/986317/abs/>).
| Version: | 0.1.6-1 |
| Imports: | Rcpp (≥ 0.12.19) |
| LinkingTo: | Rcpp |
| Published: | 2021-09-26 |
| DOI: | 10.32614/CRAN.package.nonneg.cg |
| Author: | David Cortes |
| Maintainer: | David Cortes <david.cortes.rivera at gmail.com> |
| BugReports: | https://github.com/david-cortes/nonneg_cg/issues |
| License: | BSD_2_clause + file LICENSE |
| URL: | https://github.com/david-cortes/nonneg_cg |
| NeedsCompilation: | yes |
| In views: | Optimization |
| CRAN checks: | nonneg.cg results |
| Reference manual: | nonneg.cg.pdf |
| Package source: | nonneg.cg_0.1.6-1.tar.gz |
| Windows binaries: | r-devel: nonneg.cg_0.1.6-1.zip, r-release: nonneg.cg_0.1.6-1.zip, r-oldrel: nonneg.cg_0.1.6-1.zip |
| macOS binaries: | r-release (arm64): nonneg.cg_0.1.6-1.tgz, r-oldrel (arm64): nonneg.cg_0.1.6-1.tgz, r-release (x86_64): nonneg.cg_0.1.6-1.tgz, r-oldrel (x86_64): nonneg.cg_0.1.6-1.tgz |
| Old sources: | nonneg.cg archive |
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