 

Hi R users

 

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()

 

My commands are:   nls(CV ~a*Est^b, data=limiares, start =list(a=100,b=0),
trace = TRUE)  for nonlinear regression

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

 

 

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

 

Linear regression:   Coefficients:

                                Estimate    Std. Error    t value
Pr(>|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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