[Rd] Suggestion for the optimization code
mathieu.ribatet at epfl.ch
Fri Aug 8 15:29:30 CEST 2008
Ok, please consider it as a bad call.
Thanks for your answers.
Prof Brian Ripley a écrit :
> On Fri, 8 Aug 2008, Mathieu Ribatet wrote:
>> Dear list,
>> Here's a suggestion about the different optimization code. There are several
>> optimization procedures in the base package (optim, optimize, nlm, nlminb,
>> ..). However, the output of these functions are slightly different. For
>> 1. optim returns a list with arguments par (the estimates), value the
>> minimum (maxima) of the objective function, convergence (optim
>> 2. optimize returns a list with arguments minimum (or maximum) giving
>> the estimates, objective the value of the obj. function
>> 3. nlm returns a list with arguments minimum giving the minimum of
>> the obj. function, minimum the estimates, code the optim. convergence
>> 4. nlminb returns a list with arguments par (the estimates),
>> objective, convergence (conv. code), evaluations
>> Furthermore, optim keeps the names of the parameters while nlm, nlminb don't.
>> I believe it would be nice if all these optimizers have a kind of homogenized
>> output. This will help in writing functions that can call different
>> optimizers. Obviously, we can write our own function that homogenized the
>> output after calling the optimizer, but I still believe this will be more
>> Do you think this is a reasonable feature to implement - despite it isn't an
>> important point?
> This would be essentially impossible without breaking most existing code,
> and in the case of optimize() and nlminb() that goes back many years to
> uses in S(-PLUS).
>> * BTW, if this is relevant, I could try to do it.
>> Institute of Mathematics
>> Ecole Polytechnique Fédérale de Lausanne
>> STAT-IMA-FSB-EPFL, Station 8
>> CH-1015 Lausanne Switzerland
>> Tel: + 41 (0)21 693 7907
>> R-devel at r-project.org mailing list
> Brian D. Ripley, ripley at stats.ox.ac.uk
> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
> University of Oxford, Tel: +44 1865 272861 (self)
> 1 South Parks Road, +44 1865 272866 (PA)
> Oxford OX1 3TG, UK Fax: +44 1865 272595
Institute of Mathematics
Ecole Polytechnique Fédérale de Lausanne
STAT-IMA-FSB-EPFL, Station 8
CH-1015 Lausanne Switzerland
Tel: + 41 (0)21 693 7907
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