From: Ana Quitério <ana.quiterio_at_ine.pt>

Date: Thu 26 Jan 2006 - 04:32:35 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jan 26 05:41:23 2006

Date: Thu 26 Jan 2006 - 04:32:35 EST

I'm trying to fit a model y=ax^b.

I know if I made ln(y)=ln(a)+bln(x) this is a linear regression.

But I obtain differente results with nls() and lm()

and : lm(ln_CV~ln_Est, data=limiares) for linearregression

Nonlinear regression model: a=738.2238151 and b=-0.3951013

Linear regression: Coefficients:

Estimate Std. Error t valuePr(>|t|)

(Intercept) 7.8570224 0.0103680 757.8 <2e-16 ***

ln_Est -0.5279412 0.0008658 -609.8 <2e-16 ***

I think it should be a=exp("(Intercept) ") = exp(7.8570224) = 2583.815 and b=ln_Est

Probably I'm wrong, but why??

Thanks in advance.

Ana Quiterio

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R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jan 26 05:41:23 2006

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