

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+s789695n4358800h16@n4.nabble.com
To: ii54250@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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