R help - Nov 2007 - convex optimization package for R, specifically semidefinite programming

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.

Convex optimization is a large problem domain with many interesting
new developments,  and MOSEK is a particularly good implementation
of many of these developments.  It is quite easy to get R to speak to
MOSEK via R.matlab -- i've been doing this recently for some work on  
density
estimation, but given the commercial nature of MOSEK and most of the
other convex optimization development efforts closer coordination seems
unlikely.  (I would be delighted to be proved wrong about this...)


url:    www.econ.uiuc.edu/~roger            Roger Koenker
email    rkoenker at uiuc.edu            Department of Economics
vox:     217-333-4558                University of Illinois
fax:       217-244-6678                Champaign, IL 61820


On Nov 14, 2007, at 9:31 AM, Galkowski, Jan wrote:
> 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.

>
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.
> 
>