I would be very wary of such approaches; my experience is that MM is
inferior
to the early affine-scaling versions of interior point algorithms for
linear programming
problems, and modern implementations like the Mehrotra version of the
primal dual
algorithm are much, much quicker and more reliable. More general
convex programming
is more delicate, and it is unlikely that methods that aren't that
successful with LPs
improve their performance in more complex settings. Something in R
based on CVX
or Saunder's PDCO, or similar would be very welcome. Meanwhile, as
I've said
earlier on R-help, it is fairly convenient to link these options to R
via R.matlab.
url: www.econ.uiuc.edu/~roger Roger Koenker
email [EMAIL PROTECTED] Department of Economics
vox: 217-333-4558 University of Illinois
fax: 217-244-6678 Champaign, IL 61820
On Sep 11, 2008, at 9:10 AM, Ravi Varadhan wrote:
Ken Lange's MM `algorithm' is a possibility for these non-smooth,,
convex
problems. It has been implemented in `constrOptim' for handling linear
inequality constraints in the minimization of smooth objective
functions. I
have extended this to nonlinear inequalities. It can be further
extended
for convex functions, if one can come up with a smooth function that
majorizes the convex objective function. This can be easily done
for the
absolute value function.
Ravi.
----------------------------------------------------------------------------
-------
Ravi Varadhan, Ph.D.
Assistant Professor, The Center on Aging and Health
Division of Geriatric Medicine and Gerontology
Johns Hopkins University
Ph: (410) 502-2619
Fax: (410) 614-9625
Email: [EMAIL PROTECTED]
Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html
----------------------------------------------------------------------------
--------
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
] On
Behalf Of Hans W. Borchers
Sent: Thursday, September 11, 2008 7:19 AM
To: [EMAIL PROTECTED]
Subject: Re: [R] Convex optimization in R?
Hesen Peng <hesen.peng <at> gmail.com> writes:
Hi my R buddies,
I'm trying to solve a specific group of convex optimization in R. The
admissible region is the inside and surface of a multi-dimensional
eclipse area and the goal function is the sum of absolution values of
the variables. Could any one please tell me whether there's a package
in R to do this? Thank you very much,
To my knowledge there does not exist a designated R package for convex
optimization. Also, in the Optimization task view the AMS nomenclature
90C25 for "Convex programming" (CP) is not mentioned.
On the other hand, this task view may give you some ideas on how to
solve
your problem with one of the available optimization packages.
For instance, a problem including sums of absolute values can be
modeled as
a linear program with mixed integer variables (MILP).
There is a free module for 'disciplined' convex optimization, CVX,
that can
be integrated with Matlab or Python. Hopefully, there will be a CVX R
package in the future (as has been announced/promised).
Hans Werner Borchers
ABB Corporate Research
Best wishes,
--
Hesen Peng
http://hesen.peng.googlepages.com/
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