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 <https://cvxopt.org> for more information).

Version:	0.3-1
Depends:	R (≥ 3.0.1), methods
Imports:	Rcpp (≥ 0.11.2)
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	RUnit, numDeriv
Published:	2023-12-09
DOI:	10.32614/CRAN.package.cccp
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

Documentation:

Reference manual:

cccp.pdf

Downloads:

Package source:	cccp_0.3-1.tar.gz
Windows binaries:	r-devel: cccp_0.3-1.zip, r-release: cccp_0.3-1.zip, r-oldrel: cccp_0.3-1.zip
macOS binaries:	r-release (arm64): cccp_0.3-1.tgz, r-oldrel (arm64): cccp_0.3-1.tgz, r-release (x86_64): cccp_0.3-1.tgz, r-oldrel (x86_64): cccp_0.3-1.tgz
Old sources:	cccp archive

Reverse dependencies:

Reverse depends:	FRAPO
Reverse imports:	optiSolve
Reverse suggests:	fairml, netmeta, optiSel
Reverse enhances:	CVXR

Linking:

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