thank you all for the valuable suggestions rnls() is indeed what I was looking for I've to apologize to Roger Koenker for not mentioning that I did try quantile regression (saw his answer in a previous post with a similar question, yes i did my homework) however, least medians regression gave not always satisfying results, I now understand that this is in fact due to variability in the concentrations (x-axis) (thanks to Martin Maechlers remark), my example dataset was in that sense a bit unfortunate regards Hans Vermeiren
-----Original Message----- From: Martin Maechler [mailto:[EMAIL PROTECTED] Sent: Monday, November 14, 2005 12:41 PM To: Vermeiren, Hans [VRCBE] Cc: '[email protected]'; [EMAIL PROTECTED] Subject: Re: [R] Robust Non-linear Regression Package 'sfsmisc' has had a function 'rnls()' for a while which does robust non-linear regression via M-estimation. Since you have only outliers in 'y' and none in 'x', you could use the 'nlrq' (nonlinear regression quantiles) package that Roger Koenker mentioned. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
