[R] nonlinear fitting when both x and y having measurement e
andy_liaw at merck.com
Wed Sep 12 15:43:21 CEST 2001
Would principal curves be appropriate for such problems? Packages pcurve
and princurve can do this...
> -----Original Message-----
> From: Etsushi Kato [mailto:ekato at ees.hokudai.ac.jp]
> Sent: Wednesday, September 12, 2001 8:43 AM
> To: r-help at stat.math.ethz.ch
> Cc: Prof Brian Ripley; Martyn Plummer
> Subject: Re: [R] nonlinear fitting when both x and y having
> Thank you very much Prof. Ripley and Martyn Plummer.
> Also I got one suggestion of using ORDPACK at http://www.netlib.org/.
> > > That is not a least-squares problem. Even in the simple
> linear case (one
> > > x one y) it's a hard problem, one that cannot be solved
> without more
> > > information (for example on the ratio of the error
> variances, or knowing
> > > one of them). As far as I know there is no software
> available in R for
> > > that case (although it's not hard to write).
> My data is allometric relationship of biological data, and
> perhaps it is
> OK to assume both variables having equal accuracies. So I was just
> considering using orthogonal distance to the nonlinear curve.
> > > I think you need to write down a suitable likelihood and
> optimize it
> > > numerically (with optim).
> It's a bit difficult for me to construct likelihood function, because
> right now there is no books you suggested around me...
> For the moment, I'm considering using ORDPACK. I'll try to construct
> R code later.
> Best Regards,
> Etsushi Kato
> ekato at ees.hokudai.ac.jp
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