nloptr: R Interface to NLopt

Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <http://ab-initio.mit.edu/wiki/index.php/NLopt_Introduction> for more information on the available algorithms. During installation of nloptr on Unix-based systems, the installer checks whether the NLopt library is installed on the system. If the NLopt library cannot be found, the code is compiled using the NLopt source included in the nloptr package.

Version: 1.2.1
Suggests: testthat (≥ 0.8.1), knitr, rmarkdown, inline (≥ 0.3.14)
Published: 2018-10-03
Author: Jelmer Ypma, with contributions by Hans W. Borchers and Dirk Eddelbuettel
Maintainer: Jelmer Ypma <uctpjyy at ucl.ac.uk>
License: LGPL-3
NeedsCompilation: yes
Citation: nloptr citation info
Materials: README ChangeLog
In views: Optimization
CRAN checks: nloptr results

Downloads:

Reference manual: nloptr.pdf
Vignettes: Introduction to nloptr: an R interface to NLopt
Package source: nloptr_1.2.1.tar.gz
Windows binaries: r-devel: nloptr_1.2.1.zip, r-release: nloptr_1.2.1.zip, r-oldrel: nloptr_1.2.1.zip
OS X binaries: r-release: nloptr_1.2.1.tgz, r-oldrel: nloptr_1.2.1.tgz
Old sources: nloptr archive

Reverse dependencies:

Reverse depends: CCpop, corHMM, episplineDensity, GRCdata, hisse, kergp, lineqGPR, MaxPro, OUwie, parma
Reverse imports: binaryGP, blackbox, ciuupi, cosa, diffusion, DSAIRM, dtwclust, GDINA, greybox, ICAOD, InfoTrad, lme4, mdpeer, mev, minimaxdesign, mixchar, modcmfitr, nlshrink, OptimaRegion, optiSolve, pomp, ptw, qle, RcppNLoptExample, RiskPortfolios, ROI.plugin.nloptr, RSDA, rugarch, seqHMM, smam, smooth, spaMM, SPOT, stpm, support, UncertainInterval
Reverse linking to: RcppNLoptExample
Reverse suggests: afex, CEGO, drtmle, metafor, mirt, morpheus, MSCMT, nlmixr, PortfolioAnalytics, RandomFields, regsem, RobustGaSP, SACOBRA, SuperLearner

Linking:

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