Re: [R] Non linear modeling

From: Angelo Secchi <secchi_at_sssup.it>
Date: Sat 19 Mar 2005 - 07:07:21 EST

You are right. eps in my model is not a parameter but the error term. Also the linearization doesn't solve the problem, since sometimes you cannot take logs. Any other ideas?
Thanks

On Fri, 18 Mar 2005 11:21:12 -0500
"Liaw, Andy" <andy_liaw@merck.com> wrote:

> That's treating eps as a parameter in the model. If I read your question
> right, that's not what you want.
>
> Andy
>
> > From: ronggui [mailto:0034058@fudan.edu.cn]
> >
> > then is the nls function can deal the problem as Guillaume
> > STORCHI mentioned in the last post? [X<-nls(y~x+exp(a*x)*eps,
> > data=,start=list(a=,eps=))]
> > or just can solve the problem as:log(y-x) = a*x + e?
> >
> >
> >
> > On Fri, 18 Mar 2005 08:56:38 -0500
> > "Liaw, Andy" <andy_liaw@merck.com> wrote:
> >
> > > AFAIK most model fitting techniques will only deal with
> > additive errors, not
> > > multiplicative ones. You might want to try fitting:
> > >
> > > log(y-x) = a*x + e
> > >
> > > which is linear.
> > >
> > > Andy
> > >
> > > > From: Angelo Secchi
> > > >
> > > > Hi,
> > > > is there a way in R to fit a non linear model like
> > > >
> > > > y=x+exp(a*x)*eps
> > > >
> > > > where a is the parameter and eps is the error term?
> > > > Thanks
> > > > Angelo
> > > >
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>
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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Sat Mar 19 06:12:16 2005

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