nonneg.cg: Non-Negative Conjugate-Gradient Minimizer

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

Documentation:

Reference manual: nonneg.cg.pdf

Downloads:

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

Linking:

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