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: 1.0
Depends: R (≥ 3.4.0)
Imports: methods, R6, Matrix, Rcpp (≥ 0.12.12), bit64, gmp, Rmpfr, ECOSolveR (≥ 0.5.3), scs (≥ 1.3), stats, osqp
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat, nnls, Rglpk, slam, Rmosek, gurobi, Rcplex, rcbc
Published: 2020-02-02
Author: Anqi Fu [aut, cre], Balasubramanian Narasimhan [aut], David W Kang [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_1.0.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: CVXR_1.0.tgz, r-oldrel: CVXR_1.0.tgz
Old sources: CVXR archive

Reverse dependencies:

Reverse depends: tramnet
Reverse imports: filling, Rdimtools
Reverse suggests: portfolioBacktest


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