[R] Robust fitting
Good evening,I am Marta Colombo, student of Politecnico di Milano. I'm studying Local Regression Techniques such as loess, smoothing splines and kernel smoothers. Choosing symmetric for the argument family in loess function it is possible to produce a robust estimate , in function smooth.spline and ksmooth I didn't find this possibility. Well, is there a way to produce a robust estimate using smoothing splines or kernel smoothers? And if the answer is no, why? I'm asking these questions because I need to know loess' advantages and disadvantages compared to other techniques. Thank you very much for attention, Marta Colombo __ 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
Re: [R] Robust fitting
http://www.maths.lth.se/help/R/.R/library/R.basic/html/robust.smooth.spline.html Best regards, Kristel Marta Colombo wrote: Good evening,I am Marta Colombo, student of Politecnico di Milano. I'm studying Local Regression Techniques such as loess, smoothing splines and kernel smoothers. Choosing symmetric for the argument family in loess function it is possible to produce a robust estimate , in function smooth.spline and ksmooth I didn't find this possibility. Well, is there a way to produce a robust estimate using smoothing splines or kernel smoothers? And if the answer is no, why? I'm asking these questions because I need to know loess' advantages and disadvantages compared to other techniques. Thank you very much for attention, Marta Colombo __ 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 Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm __ 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
Re: [R] Robust fitting
Note: As I believe Brian Ripley pointed out in his MASS book, loess may not be as resistant to outliers (which is one aspect of robustness; robustness of efficiency is another) as you think. The problem is that it starts off with LS estimates and these can be so distorted by unusual values that the reweighting cannot properly recover; i.e. convergence is to a local minimum far from the desired global one. You might wish to read the documentation for rlm() (in MASS, the package) and the appropriate sections of MASS, the book. Cheers, -- Bert Gunter Genentech Non-Clinical Statistics South San Francisco, CA The business of the statistician is to catalyze the scientific learning process. - George E. P. Box -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Marta Colombo Sent: Monday, November 28, 2005 10:38 AM To: R help Subject: [R] Robust fitting Good evening,I am Marta Colombo, student of Politecnico di Milano. I'm studying Local Regression Techniques such as loess, smoothing splines and kernel smoothers. Choosing symmetric for the argument family in loess function it is possible to produce a robust estimate , in function smooth.spline and ksmooth I didn't find this possibility. Well, is there a way to produce a robust estimate using smoothing splines or kernel smoothers? And if the answer is no, why? I'm asking these questions because I need to know loess' advantages and disadvantages compared to other techniques. Thank you very much for attention, Marta Colombo __ 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 __ 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