From ripley at stats.ox.ac.uk  Fri Aug  8 15:26:43 2008
From: ripley at stats.ox.ac.uk (Prof Brian Ripley)
Date: Fri, 8 Aug 2008 14:26:43 +0100 (BST)
Subject: [Rd] Suggestion for the optimization code
In-Reply-To: <489C4293.2080806@epfl.ch>
References: <489C4293.2080806@epfl.ch>
Message-ID: <alpine.LFD.1.10.0808081405100.7967@gannet.stats.ox.ac.uk>

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 
> instance,
>
>  1. optim returns a list with arguments par (the estimates), value the
>     minimum (maxima) of the objective function, convergence (optim
>     .convergence)
>  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.
> s
> 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 
> user-friendly.
>
> 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).

> Best,
> Mathieu
>
> * BTW, if this is relevant, I could try to do it.
>
> -- 
> Institute of Mathematics
> Ecole Polytechnique F?d?rale de Lausanne
> STAT-IMA-FSB-EPFL, Station 8
> CH-1015 Lausanne   Switzerland
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> Tel: + 41 (0)21 693 7907
>
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>

-- 
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


[Rd] Suggestion for the optimization code
Prof Brian Ripley