[R] nonlinear regression with M estimation
Prof Brian Ripley
ripley at stats.ox.ac.uk
Mon Jul 5 18:31:52 CEST 2004
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 at 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
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