It is not homework. My problem is this: I used nonlinear regression to fit a
lognormal cumulative distribution to the probability of a buildings' collapse
against a measure of seismic intensity. I am able to obtain the asymptotic
confidence intervals. I am not , however, certain that they are accurate and I
wonder whether a bootstrap or even a Monte carlo could improve their accuracy.
You see I want a realistic represntation of the confidence intervals as I need
to propagate it further in the risk assessment. Perhaps I m wrong. Could you
please enlighten me?
Yanna
Date: Sun, 5 Feb 2012 03:42:05 -0800
From: ml-node+s789695n4358800...@n4.nabble.com
To: ii54...@msn.com
Subject: Re: plotting confidence bands from predict.nls
On 05/02/2012 08:10, ioanna wrote:
> How do you use bootstrap to estimate the confidence as well as the prediction
> intervals in nonlinear regression ?
With difficulty!
There is far too little here to go on, and this seems an odd question
unless it is homework (why dictate a problem-strewn method of solution
if this is a real problem?)
The real issue is how to bootstrap nonlinear regression, and you will
find that discussed in all good books on the subject, such as Venables &
Ripley and Davison & Hinkley. It is not trivial and the solutions are
not altogether satisfactory ....
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--
Brian D. Ripley, [hidden email]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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