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 |
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 imports: | gpDDE |
Reverse suggests: | bayesGDS, sparseMVN |
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