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: 0.8.6
Depends: R (≥ 3.1.2)
Imports: Matrix (≥ 1.2.8), Rcpp (≥ 0.12.8), methods
LinkingTo: Rcpp, RcppEigen (≥ 0.3.2.9.1)
Suggests: testthat, knitr
Published: 2017-04-26
Author: Michael Braun [aut, cre, cph]
Maintainer: Michael Braun <braunm at smu.edu>
License: MPL (≥ 2.0)
Copyright: (c) 2015-2017 Michael Braun
URL: http://coxprofs.cox.smu.edu/braunm
NeedsCompilation: yes
SystemRequirements: C++11
Citation: trustOptim citation info
Materials: NEWS
In views: Optimization
CRAN checks: trustOptim results

Downloads:

Reference manual: trustOptim.pdf
Vignettes: Using trustOptim
Quick demo
Package source: trustOptim_0.8.6.tar.gz
Windows binaries: r-devel: trustOptim_0.8.6.zip, r-release: trustOptim_0.8.6.zip, r-oldrel: trustOptim_0.8.6.zip
OS X El Capitan binaries: r-release: trustOptim_0.8.6.tgz
OS X Mavericks binaries: r-oldrel: trustOptim_0.8.6.tgz
Old sources: trustOptim archive

Reverse dependencies:

Reverse imports: gpDDE
Reverse suggests: bayesGDS, sparseMVN

Linking:

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