[R] fast optimizer
Prof. John C Nash
nashjc at uottawa.ca
Fri Oct 30 14:48:34 CET 2009
> Date: Fri, 30 Oct 2009 09:29:06 +0100
> From: Christophe Dutang <dutangc at gmail.com>
> Subject: Re: [R] [R-SIG-Finance] Fast optimizer
> To: R_help Help <rhelpacc at gmail.com>
> Cc: r-help at r-project.org
>> > Ok. I have the following likelihood function.
>> >
>> > L <- p*dpois(x,a)*dpois(y,b+c)+(1-p)*dpois(x,a+c)*dpois(y,b)
>> >
>> > where I have 100 points of (x,y) and parameters c(a,b,c,p) to
>> > estimate. Constraints are:
>> >
>> > 0 < p < 1
>> > a,b,c > 0
>> > c < a
>> > c < b
>> >
>> > I construct a loglikelihood function out of this. First ignoring the
>> > last two constraints, it takes optim with box constraint about 1-2 min
>> > to estimate this. I have to estimate the MLE on about 200 rolling
>> > windows. This will take very long. Is there any faster implementation?
> Take a look at the CRAN task view on optimisation, you may find faster
> algorithms.
>
There are several new or revised methods in development as well as a new
wrapper optimx() in the r-forge OptimizeR project
http://r-forge.r-project.org/R/?group_id=395
In particular Rvmmin is an all-R implementation of the algorithm at the
heart of optim's BFGS but with bounds and mask (fixed parameter)
constraints. I'm looking into how it can be made more convenient to
hot-start with suspected "good" parameters, which would be likely be
important here.
JN
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