Package: psqn 0.3.2

psqn: Partially Separable Quasi-Newton

Provides quasi-Newton methods to minimize partially separable functions. The methods are largely described by Nocedal and Wright (2006) <doi:10.1007/978-0-387-40065-5>.

Authors:Benjamin Christoffersen [cre, aut]

psqn_0.3.2.tar.gz
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psqn_0.3.2.tgz(r-4.6-x86_64)psqn_0.3.2.tgz(r-4.6-arm64)psqn_0.3.2.tgz(r-4.5-x86_64)psqn_0.3.2.tgz(r-4.5-arm64)
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psqn_0.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
psqn/json (API)

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

Bug tracker:https://github.com/boennecd/psqn/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

optimizationoptimization-algorithmsquasi-newtonopenblascppopenmp

4.78 score 2 stars 1 packages 6 scripts 400 downloads 7 exports 28 dependencies

Last updated from:ba9d4c9964. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK161
linux-devel-x86_64OK203
source / vignettesOK224
linux-release-arm64OK162
linux-release-x86_64OK166
macos-release-arm64OK203
macos-release-x86_64OK412
macos-oldrel-arm64OK164
macos-oldrel-x86_64OK337
windows-devel-arm64OK508
windows-devel-x86_64OK242
windows-release-arm64OK440
windows-release-x86_64OK210
windows-oldrel-x86_64OK199
wasm-releaseOK105

Exports:psqnpsqn_aug_Lagrangpsqn_aug_Lagrang_genericpsqn_bfgspsqn_genericpsqn_generic_hesspsqn_hess

Dependencies:briocallrclicrayondescdiffobjevaluatefsgluejsonlitelatticelifecyclemagrittrMatrixotelpkgbuildpkgloadpraiseprocessxpsR6RcppRcppEigenrlangrprojroottestthatwaldowithr

A Quick Introduction to the psqn Package
The R Interface | The R Interface for optimizer_generic | Ending Remarks
Rendered fromquick-intro.html.asisusingR.rsp::asis

Last update: 2020-11-04
Started: 2020-11-04

psqn: Partially Separable Quasi-Newton
Example | Quasi-Newton Method for Partially Separable Functions | Conjugate Gradient Method | Line Search and Wolfe Condition | Symmetric Rank-one Updates | Example Using the Implementation | Details | References
Rendered frompsqn.html.asisusingR.rsp::asis

Last update: 2020-10-20
Started: 2020-10-20