Re: [R] nonlinear regression with M estimation

From: Prof Brian Ripley <>
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,        
Professor of Applied Statistics,
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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Received on Tue Jul 06 02:34:51 2004

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