Duncan Murdoch wrote:
On 8/8/2008 8:56 AM, 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.
Unfortunately, changing the names within the return value would break a
lot of existing uses of those functions. Writing a wrapper to
homogenize the output is probably the right thing to do.
And potentially to harmonize inputs. The MLInterfaces package
(Bioconductor) has done this for many machine learning algorithms,
should you want an example to look at.
Robert
Duncan Murdoch
Do you think this is a reasonable feature to implement - despite it
isn't an important point?
Best,
Mathieu
* BTW, if this is relevant, I could try to do it.
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Robert Gentleman, PhD
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
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