Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Anqi Fu, Balasubramanian Narasimhan, Stephen Boyd
Title: CVXR: An R Package for Disciplined Convex Optimization
Abstract: CVXR is an R package that provides an object-oriented modeling language for convex optimization, similar to CVX, CVXPY, YALMIP, and Convex.jl. It allows the user to formulate convex optimization problems in a natural mathematical syntax rather than the restrictive form required by most solvers. The user specifies an objective and set of constraints by combining constants, variables, and parameters using a library of functions with known mathematical properties. CVXR then applies signed disciplined convex programming (DCP) to verify the problem's convexity. Once verified, the problem is converted into standard conic form using graph implementations and passed to a cone solver such as ECOS or SCS. We demonstrate CVXR's modeling framework with several applications.

Page views:: 1777. Submitted: 2017-12-01. Published: 2020-09-13.
Paper: CVXR: An R Package for Disciplined Convex Optimization     Download PDF (Downloads: 825)
CVXR_1.0-8.tar.gz: R source package Download (Downloads: 48; 974KB) Replication materials Download (Downloads: 52; 27KB)

DOI: 10.18637/jss.v094.i14

This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.