[R] Convex optimization in R?

[Hesen Peng]

Well, I finally figured out to do some algebra transformation and the
problem was reduced to non-linear optimization on bounded areas. But
on my way to this I ran into IMSL Fortran library function NNLPF. And
its documentation toke me to DONLP2, a free Fortran package solving a
huge family of nonlinear optimization problems.

However, I just had great difficulty understanding the comments and
integrating them to form an R subroutine. Maybe someone can do this in
the future.

On Thu, Sep 11, 2008 at 10:32 AM, roger koenker <rkoenker at uiuc.edu> wrote:
> 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    rkoenker at uiuc.edu            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: rvaradhan at jhmi.edu
>>
>> Webpage:  http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html
>>
>>
>>
>>
>> ----------------------------------------------------------------------------
>> --------
>>
>>
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
>> On
>> Behalf Of Hans W. Borchers
>> Sent: Thursday, September 11, 2008 7:19 AM
>> To: r-help at stat.math.ethz.ch
>> 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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>>
>> ______________________________________________
>> R-help at r-project.org mailing list
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>> PLEASE do read the posting guide
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>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> 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.
>



-- 
彭河森 Hesen Peng
http://hesen.peng.googlepages.com/