Re: [R] nonlinear regression with M estimation

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Tue 06 Jul 2004 - 02:31:52 EST


I don't think there is one. One problem is that both nls and robust procedures need a starting point and so you would need a good non-linear resistant method to start. (For certain Huber-type linear regressions you can show there is a unique solution and so any starting point will do. But that is rather unusual.)

The nearest equivalent I can think of is package nlrq, which also needs suitable starting values. Once you have those, you could just call optim to minimize the log-likelihood under the Huber long-tailed model.

On Mon, 5 Jul 2004, Ruei-Che Liu wrote:

> Could any one tells me if R or S has the capacity to fit nonlinear
> regression with Huber's M estimation? Any suggestion is appreciated. I was
> aware of 'rlm' in MASS library for robust linear regression and 'nls' for
> nonlinear least squares regression, but did not seem to be able to find
> robust non-linear regression function.

-- 
Brian D. Ripley,                  ripley@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

______________________________________________
R-help@stat.math.ethz.ch mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Received on Tue Jul 06 02:34:51 2004

This archive was generated by hypermail 2.1.8 : Wed 03 Nov 2004 - 22:54:43 EST