Hi All, 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. Thanks and regards, Ray Liu
the package nlrq does median nonlinear regression... among other things. url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820 On Jul 5, 2004, at 11:08 AM, Ruei-Che Liu wrote:> Hi All, > 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. > > Thanks and regards, > > Ray Liu > > ______________________________________________ > R-help at 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
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