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:Please use the canonical form https://CRAN.R-project.org/package=nonneg.cg to link to this page.
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