Package: nonneg.cg 0.1.6-1

David Cortes

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/>).

Authors:David Cortes

nonneg.cg_0.1.6-1.tar.gz
nonneg.cg_0.1.6-1.tar.gz(r-4.5-noble)nonneg.cg_0.1.6-1.tar.gz(r-4.4-noble)
nonneg.cg_0.1.6-1.tgz(r-4.4-emscripten)nonneg.cg_0.1.6-1.tgz(r-4.3-emscripten)
nonneg.cg.pdf |nonneg.cg.html
nonneg.cg/json (API)

# Install 'nonneg.cg' in R:
install.packages('nonneg.cg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/david-cortes/nonneg_cg/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

1.00 score 1 scripts 238 downloads 1 exports 1 dependencies

Last updated 3 years agofrom:f352d4ddac. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-linux-x86_64OKNov 11 2024

Exports:minimize.nonneg.cg

Dependencies:Rcpp