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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 <https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/> for more information on the available algorithms. Building from included sources requires 'CMake'. On Linux and 'macOS', if a suitable system build of NLopt (2.7.0 or later) is found, it is used; otherwise, it is built from included sources via 'CMake'. On Windows, NLopt is obtained through 'rwinlib' for 'R <= 4.1.x' or grabbed from the appropriate toolchain for 'R >= 4.2.0'.

Version: 2.1.1
Suggests: knitr, rmarkdown, covr, tinytest
Published: 2024-06-25
DOI: 10.32614/CRAN.package.nloptr
Author: Jelmer Ypma [aut], Steven G. Johnson [aut] (author of the NLopt C library), Aymeric Stamm ORCID iD [ctb, cre], Hans W. Borchers [ctb], Dirk Eddelbuettel [ctb], Brian Ripley [ctb] (build process on multiple OS), Kurt Hornik [ctb] (build process on multiple OS), Julien Chiquet [ctb], Avraham Adler ORCID iD [ctb], Xiongtao Dai [ctb], Jeroen Ooms [ctb]
Maintainer: Aymeric Stamm <aymeric.stamm at cnrs.fr>
BugReports: https://github.com/astamm/nloptr/issues
License: LGPL (≥ 3)
URL: https://github.com/astamm/nloptr, https://astamm.github.io/nloptr/
NeedsCompilation: yes
SystemRequirements: cmake (>= 3.2.0) which is used only on Linux or macOS systems when no system build of nlopt (>= 2.7.0) can be found.
Citation: nloptr citation info
Materials: README NEWS
In views: Optimization
CRAN checks: nloptr results

Documentation:

Reference manual: nloptr.pdf
Vignettes: nloptr

Downloads:

Package source: nloptr_2.1.1.tar.gz
Windows binaries: r-devel: nloptr_2.1.1.zip, r-release: nloptr_2.1.1.zip, r-oldrel: nloptr_2.1.1.zip
macOS binaries: r-release (arm64): nloptr_2.1.1.tgz, r-oldrel (arm64): nloptr_2.1.1.tgz, r-release (x86_64): nloptr_2.1.1.tgz, r-oldrel (x86_64): nloptr_2.1.1.tgz
Old sources: nloptr archive

Reverse dependencies:

Reverse depends: CNORfuzzy, corHMM, GRCdata, hisse, kergp, LinkedGASP, MaxPro, NMMIPW, OUwie, PAIRADISE, parma, pgsc, soilhypfit, surveyvoi, WRSS
Reverse imports: adoptr, ANCOMBC, asremlPlus, BayesianMCPMod, binaryGP, blackbox, BRcal, cauphy, ciuupi, ciuupi2, ClinicalUtilityRecal, complex, ConsReg, cops, cosa, CoSMoS, depCensoring, DGLMExtPois, diffusion, dirttee, do3PCA, DPpack, DSAIDE, DSAIRM, EquiTrends, ExGaussEstim, ExtremalDep, EzGP, fdacluster, ffp, ForestDisc, foretell, FTSgof, fucom, garma, gasmodel, GDINA, gimme, gllvm, greybox, gscreend, GUILDS, hawkesbow, hbal, HiGarrote, highOrderPortfolios, hyperbolicDEA, ICAOD, InfoTrad, Infusion, junctions, ldmppr, legion, lme4, logitr, LPsmooth, ltable, maxstablePCA, mdpeer, MetaHD, MHD, missSBM, mixchar, mlt, mosqcontrol, mrds, MSTest, nebula, nlshrink, OptimalGoldstandardDesigns, OptimaRegion, optimx, optiSolve, phyr, PINstimation, PLNmodels, PNAR, PoA, power.transform, ptable, Qval, RAREsim, RcppNLoptExample, reservr, retel, riskParityPortfolio, RiskPortfolios, rkriging, rMOST, RNAdecay, RobustCalibration, RobustGaSP, Robyn, ROI.plugin.nloptr, rpm, rrscale, RSDA, rugarch, SAMGEP, semlbci, seqHMM, sharp, signeR, smam, smooth, spaMM, spant, stops, stpm, Summix, survELtest, SurvSparse, TCA, TesiproV, TidyDensity, TOHM, TopKSignal, treestats, tsgarch, tsmarch, twingp, Unico
Reverse linking to: fdacluster, junctions, missSBM, PLNmodels, RcppNLoptExample, rkriging, surveyvoi, treestats, twingp
Reverse suggests: afex, apsimx, bbotk, castor, CEGO, cxr, drtmle, metafor, mirt, mlr3mbo, mlr3pipelines, mlr3tuning, MSCMT, nimble, nlmixr2est, optiSel, PerformanceAnalytics, pomp, PortfolioAnalytics, regsem, sense, sirt, smof, SuperLearner, swdft, wflo

Linking:

Please use the canonical form https://CRAN.R-project.org/package=nloptr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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