It is not at all clear what you are trying to do. Fitting a gaussian distribution is the simplest problem in all of statistics: the sample mean and sample variance (divisor n) are the mle's of the two parameters involved. No non-linear regresson is required.
If what you are really trying to do is fit a (normalized?) gaussian probability density function as a form of non-linear regression, i.e. by least squares, that is an entirely different problem. I'm a bit stumped as to how this form of non-linear regresion should arise, particularly with equal variance both for values near the mode as well as in the tails, but stranger things have happened, I suppose. What I would do is, if you response values are non-negative, take logs and regress using a quadratic regression model, and then identify the approximate mean and variance parameters, which should then be reasonable starting values for the non-linear regression. Negative responses will pose a problem, of course. Bill Venables. ________________________________________ From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] On Behalf Of Antje [niederlein-rs...@yahoo.de] Sent: 14 July 2009 17:21 To: r-h...@stat.math.ethz.ch Subject: [R] nls - find good starting values Hi there, it might be a very simple question and I'd be glad to even get a link to some useful documentation... I have several data sets, I'd like to fit to a gaussian distribution. I've tried to give an estimate of the mean and the sd of this distribution but still, I run into problems if these estimates are not close enough. For example, nls() breaks with this message: singular gradient matrix at initial parameter estimates I don't know how to avoid these bad start values because their estimate is automated. Better start values are often quite close. I was wondering whether there is any way to test several start-values as long as nls does not succeed. I would do it with a while construct but maybe there is another approach? Any hint is very welcome! Ciao, Antje ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
