> Hi there, I do assume you are talking about the CVXOPT (and CVXMOD) Python package(s). Please note that CVXOPT only contains _interfaces_ to the solvers in MOSEK, because these are commercial products (as Roger Koenker already has mentioned).
There appear to be some Python/Scipy-based solvers available in CVXOPT, but for larger applications one would still have to utilize the original CVX modules. CVX itself is a free "Matlab software for disciplined convex optimization". As you can read on their Web page <http://www.stanford.edu/~boyd/cvx/>, future plans are to port it to other frameworks such as *R*, Octave, or Mathematica. Perhaps the R community could accelerate such an R port by contacting the developers and by offering support and provision (I can't, I'm no programmer, I am only modeling and trying to solve optimization problems). -- Hans Werner Galkowski, Jan <jgalkows <at> akamai.com> writes: > > Recently, a package for convex optimization was announced for Python, > based upon the LP solver GLPK, the SDP solver > in DSDP5, and the LP and QP solvers in MOSEK. I'm aware GLPK is > available for R, but wondered if anyone had good > packages for convex optimization along these lines for R. > > TIA. > > ______________________________________________ > R-help <at> r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.