cccp: Cone Constrained Convex Problems

Routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms are partially ported from CVXOPT, a Python module for convex optimization (see <http://cvxopt.org> for more information).

Version: 0.2-7
Depends: R (≥ 3.0.1), methods
Imports: Rcpp (≥ 0.11.2)
LinkingTo: Rcpp, RcppArmadillo
Suggests: RUnit, numDeriv
Published: 2020-10-30
Author: Bernhard Pfaff [aut, cre], Lieven Vandenberghe [cph] (copyright holder of cvxopt), Martin Andersen [cph] (copyright holder of cvxopt), Joachim Dahl [cph] (copyright holder of cvxopt)
Maintainer: Bernhard Pfaff <bernhard at pfaffikus.de>
License: GPL (≥ 3)
NeedsCompilation: yes
In views: Optimization
CRAN checks: cccp results

Downloads:

Reference manual: cccp.pdf
Package source: cccp_0.2-7.tar.gz
Windows binaries: r-devel: cccp_0.2-7.zip, r-devel-UCRT: cccp_0.2-7.zip, r-release: cccp_0.2-7.zip, r-oldrel: cccp_0.2-7.zip
macOS binaries: r-release (arm64): cccp_0.2-7.tgz, r-release (x86_64): cccp_0.2-7.tgz, r-oldrel: cccp_0.2-7.tgz
Old sources: cccp archive

Reverse dependencies:

Reverse depends: FRAPO
Reverse imports: optiSolve
Reverse enhances: CVXR

Linking:

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