From: Spencer Graves <spencer.graves_at_pdf.com>

Date: Fri 17 Feb 2006 - 15:25:56 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Feb 17 15:29:46 2006

Date: Fri 17 Feb 2006 - 15:25:56 EST

- You will always get more accurate answers from profiling than from the Wald "pseudodesign matrix" approach. Moreover, often the differences are dramatic.
- I just did RSiteSearch("profiling with nls"). The first hit was "http://finzi.psych.upenn.edu/R/library/stats/html/profile.nls.html". If this is not satisfactory, please explain why.

hope this helps. spencer graves

Murray Jorgensen wrote:

> Given a nonlinear model formula and a set of values for all the

*> parameters defining a point in parameter space, is there a neat way to
**> extract the pseudodesign matrix of the model at the point? That is the
**> matrix of partial derivatives of the fitted values w.r.t. the parameters
**> evaluated at the point.
**>
**> (I have figured out how to extract the gradient information from an nls
**> fitted model using the nlsModel part, but I wish to implement a score
**> test, so I need to be able to extract the information at points other
**> than the mle.)
**>
**> Thanks, Murray Jorgensen
*

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Feb 17 15:29:46 2006

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