From: Murray Jorgensen <maj_at_stats.waikato.ac.nz>

Date: Fri 17 Feb 2006 - 18:23:15 EST

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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 18:29:01 2006

Date: Fri 17 Feb 2006 - 18:23:15 EST

I have been able to carry out the test by extracting

Spencer Graves wrote:

> There doubtless is a way to extract the gradient information you

*> desire, but have you considered profiling instead? Are you familiar
**> with the distinction between intrinsic and parameter effects curvature?
**> In brief, part of the nonlinearities involved in nonlinear least
**> squares are intrinsic to the problem, and part are due to the how the
**> problem is parameterized. If you change the parameterization, you
**> change the parameter effects curvature, but the intrinsic curvature
**> remains unchanged. Roughly 30 years ago, Doug Bates and Don Watts
**> reanalized a few dozen published nonlinear regression fits, and found
**> that in all but perhaps one or two, the parameter effects were dominant
**> and the intrinsic curvature was negligible. See Bates and Watts (1988)
**> Nonlinear Regression Analysis and Its Applications (Wiley) or Seber and
**> Wild (1989) Nonlinear Regression (Wiley).
**>
**> Bottom line:
**>
**> 1. You will always get more accurate answers from profiling than
**> from the Wald "pseudodesign matrix" approach. Moreover, often the
**> differences are dramatic.
**>
**> 2. 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 -- Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: maj@waikato.ac.nz Fax 7 838 4155Phone +64 7 838 4773 wk Home +64 7 825 0441 Mobile 021 1395 862

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 18:29:01 2006

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