Re: [R] Avoiding another loop

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Subject: Re: [R] Avoiding another loop
From: Michael Roberts (mroberts@ers.usda.gov)
Date: Tue 30 Jan 2001 - 04:34:23 EST 

Message-Id: <sa757182.072@ers.usda.gov>

Sorry, I can now see why I needed to provide more information.

I am trying to use simulation to estimate a likelihood function
that cannot be evaluated explicitly: a multinomial probit model
with a spatail autocorrelation parameter for each latent dependent
variable. "myfunction" generates a single latent observation (for
all latent
dependent variables less one) for a parameter guess. Clearly, I
need
to do this many times to get an accurate estimate of the likelihood.

Is a loop the best way to do this?

Thanks much,

Michael J. Roberts
Resource Economics Division, PMT
USDA-ERS
202-694-5557

>>> Prof Brian D Ripley <ripley@stats.ox.ac.uk> 01/29 1:16 PM >>>
On Mon, 29 Jan 2001, Michael Roberts wrote:

> Hello,
>
> Is there a fancy way I can use a function (like apply)
> to avoid a the follwoing loop, or otherwise make this more
> efficient? It fills a 3-d array, one matrix at a time.
> "nsize" is big, and efficiency is important.
>
> for (i in 1:nsize) simy[,,i] <- myfunction(p1,p2, ...)
>

You will need to tell us a lot more. At present it appears that you
are
doing the same calculation nsize times, which is of course easy to
avoid.

Avoiding loops in R is by no mean always useful or effective. There
are
myths about that go back to long-forgotten versions of S, in which
for
loops were very much to be avoided. Up to a point *vectorization*
is
worthwhile, the point being where handling large vectors becones
expensive. 

-- 
Brian D. Ripley,                  ripley@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 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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