[R] Non linear modeling

[Angelo Secchi]

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 at 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 at 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 at 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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