CVXR: Disciplined Convex Optimization

An object-oriented modeling language for disciplined convex programming (DCP). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution.

Version: 0.94-4
Depends: R (≥ 3.4.0)
Imports: methods, R6, Matrix, Rcpp (≥ 0.12.12), bit64, gmp, Rmpfr, R.utils, ECOSolveR, scs, stats
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat, nnls
Published: 2017-11-20
Author: Anqi Fu [aut, cre], Balasubramanian Narasimhan [aut], Steven Diamond [aut], John Miller [aut], Stephen Boyd [ctb], Paul Kunsberg Rosenfield [ctb]
Maintainer: Anqi Fu <anqif at stanford.edu>
BugReports: https://github.com/anqif/CVXR/issues
License: Apache License 2.0 | file LICENSE
URL: https://cvxr.rbind.io, https://github.com/anqif/CVXR
NeedsCompilation: yes
Materials: README
In views: Optimization
CRAN checks: CVXR results

Downloads:

Reference manual: CVXR.pdf
Vignettes: Disciplined Convex Optimization
Package source: CVXR_0.94-4.tar.gz
Windows binaries: r-devel: CVXR_0.94-4.zip, r-release: CVXR_0.94-4.zip, r-oldrel: not available
OS X El Capitan binaries: r-release: CVXR_0.94-4.tgz
OS X Mavericks binaries: r-oldrel: not available

Reverse dependencies:

Reverse imports: filling

Linking:

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