trustOptim: Trust Region Optimization for Nonlinear Functions with Sparse Hessians

Trust region algorithm for nonlinear optimization. Efficient when the Hessian of the objective function is sparse (i.e., relatively few nonzero cross-partial derivatives). See Braun, M. (2014) <doi:10.18637/jss.v060.i04>.

Version: 0.8.7.3
Depends: R (≥ 3.6)
Imports: Matrix (≥ 1.2.18), Rcpp (≥ 1.0.3), methods
LinkingTo: Rcpp, RcppEigen (≥ 0.3.3.7.0)
Suggests: testthat, knitr
Published: 2021-10-11
Author: Michael Braun ORCID iD [aut, cre, cph]
Maintainer: Michael Braun <braunm at smu.edu>
BugReports: https://github.com/braunm/trustOptim/issues
License: MPL (≥ 2.0)
Copyright: (c) 2015-2021 Michael Braun
URL: https://braunm.github.io/trustOptim/, https://github.com/braunm/trustOptim/
NeedsCompilation: yes
SystemRequirements: C++11
Citation: trustOptim citation info
Materials: NEWS
In views: Optimization
CRAN checks: trustOptim results

Documentation:

Reference manual: trustOptim.pdf
Vignettes: Using trustOptim
Quick demo

Downloads:

Package source: trustOptim_0.8.7.3.tar.gz
Windows binaries: r-devel: trustOptim_0.8.7.3.zip, r-release: trustOptim_0.8.7.3.zip, r-oldrel: trustOptim_0.8.7.3.zip
macOS binaries: r-release (arm64): trustOptim_0.8.7.3.tgz, r-oldrel (arm64): trustOptim_0.8.7.3.tgz, r-release (x86_64): trustOptim_0.8.7.3.tgz
Old sources: trustOptim archive

Reverse dependencies:

Reverse imports: sfaR, ZIPFA
Reverse suggests: aghq, sparseMVN

Linking:

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