Re: [R] standard errors for predict.nls?

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Mon, 03 Nov 2008 16:37:44 +0000 (GMT)

On Mon, 3 Nov 2008, Ben Bolker wrote:

> Christoph Scherber <Christoph.Scherber <at> agr.uni-goettingen.de> writes:
>
>>
>> Dear all,
>>
>> Is there a way to retrieve standard errors from nls models?
>> The help page tells me that arguments
>> such as se.fit are ignored...
>>
>> Many thanks and best wishes
>> Christoph
>
> I have written some reasonably generic
> delta-function code that can in principle
> do this. I have been thinking about contributing it, if R-core
> thinks it's worthwhile, but I haven't gotten around to incorporating
> it into a version of predict.nls yet. In the meantime, if you

In general using the delta method (which is I guess what you mean, local linearization via derivatives) is nowhere near accurate enough to be useful. That's why it has not been done on several occasions in the past. If you think it might be, see ?delta.method in package alr3.

I would suggest using simulation/bootsrapping to explore the uncertainty. There is an example in MASS of doing so (and that illustrates some of the pitfalls).

> install the emdbook package and look at ?deltavar, you may
> be able to get that to work for you ... (if not, get back in
> touch & I'll try to help -- maybe this will be the impetus
> to develop that code a bit more).
>
> cheers
> Ben Bolker
>
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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

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Received on Mon 03 Nov 2008 - 16:40:07 GMT

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