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: 0.99-7
Depends: R (≥ 3.4.0)
Imports: methods, R6, Matrix, Rcpp (≥ 0.12.12), bit64, gmp, Rmpfr, R.utils, ECOSolveR (≥ 0.5.3), scs (≥ 1.3), stats
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat, nnls, reticulate, lpSolveAPI, Rglpk, slam
Published: 2019-11-07
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>
License: Apache License 2.0 | file LICENSE
NeedsCompilation: yes
Materials: README NEWS
In views: Optimization
CRAN checks: CVXR results


Reference manual: CVXR.pdf
Vignettes: Disciplined Convex Optimization
Package source: CVXR_0.99-7.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: CVXR_0.99-7.tgz, r-oldrel: CVXR_0.99-7.tgz
Old sources: CVXR archive

Reverse dependencies:

Reverse imports: filling, Rdimtools
Reverse suggests: portfolioBacktest, updog


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