[R] fitting models with gnls

[Antonio Olinto]

Dear Bates and Dalgaard,

Thanks for your attention. Removing the brackets I could fit the model.

Sincerely,

Antonio Olinto

----- Original Message -----
From: "Douglas Bates" <bates at stat.wisc.edu>
To: "Antonio Olinto" <aolinto at bignet.com.br>
Cc: "R-help" <r-help at stat.math.ethz.ch>
Sent: Friday, September 07, 2001 2:17 PM
Subject: Re: [R] fitting models with gnls


> "Antonio Olinto" <aolinto at bignet.com.br> writes:
>
> > Dear R-list members,
>
> > Some months ago I wrote a message on the usage of gnls (nlme
> > library) and here I come again.
>
> Sorry about the delay.  As some people have noticed, I am seriously
> over-committed right now and it is difficult to find time to look at
> problems with the R version of nlme.
>
> As Peter Dalgaard said, the problem is in an assignment of the form
>   fact[] <- value
> where fact is a factor.  The particular line that is giving the
> problem is in the gnls function itself
>         grpShrunk[] <- grpShrunk[revOrderShrunk]
>
> If you remove the first set of brackets, so it reads
>         grpShrunk <- grpShrunk[revOrderShrunk]
> you can fit your model in R.
>
> > growth.gnls <- gnls(lt ~ Linf*(1-exp(-K*(age-t0))),
> +   data=growth.dat, params= Linf +K + t0 ~ 1,
start=list(Linf=500,K=0.2,t0=0),
> +   control = list(returnObject = T), corr = corAR1(form=~fish|age))
> > summary(growth.gnls)
> Generalized nonlinear least squares fit
>   Model: lt ~ Linf * (1 - exp(-K * (age - t0)))
>   Data: growth.dat
>        AIC      BIC    logLik
>   757.3853 770.4112 -373.6927
>
> Correlation Structure: AR(1)
>  Formula: ~fish | age
>  Parameter estimate(s):
>        Phi
> 0.04672911
>
> Coefficients:
>         Value Std.Error  t-value p-value
> Linf 509.7454  8.278899 61.57164  <.0001
> K      0.1988  0.007966 24.95591  <.0001
> t0     0.2987  0.046531  6.41996  <.0001
>
>  Correlation:
>    Linf   K
> K  -0.963
> t0 -0.647  0.783
>
> Standardized residuals:
>        Min         Q1        Med         Q3        Max
> -1.7863143 -0.5340824 -0.1925364  0.3771429  2.5162105
>
> Residual standard error: 10.32122
> Degrees of freedom: 100 total; 97 residual
>
> I agree with Peter that this is best fixed by changing [<-.factor in
> R.  The temporary fix is to create a private copy of gnls and make the
> change described above.  I would prefer not to make a permanent change
> like that in the nlme package.
>

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