[R] nlme questions

[Christian Mora]

Spencer;

Thanks for your suggestions. I found the problem is in the library nlme. If
you define phi1~factor(trt1)+factor(trt2) instead of phi1~trt1+trt2 the
augPred function works. A bug? I don't know.

Christian






Spencer Graves <spencer.graves at pdf.com> on 17-11-2005 20:19:32

To:    Christian Mora <christian_mora at arauco.cl>
cc:    r-help at stat.math.ethz.ch

Subject:    Re: [R] nlme questions


   Both your questions seem too vague to me.  You might get more useful
replies if you provide a simple example in a few lines of R code that a
reader could copy from your email into R and see the result (as
suggested in the posting guide! "www.R-project.org/posting-guide.html").
  The process of preparing such a simple example might by itself provide
the insight you desire.  Alternatively, you might work line by line
through the code for the R function you are using.  Also, if you don't
have Pinheiro and Bates (2000) Mixed-Effects Models in S and S-PLUS
(Springer), I suggest you get it;  it is excellent for things like this.

   I'm sorry I couldn't help more.
   spencer graves

Christian Mora wrote:

>
>
>
> Dear R users;
>
> Ive got two questions concerning nlme library 3.1-65 (running on R 2.2.0
/
> Win XP Pro). The first one is related to augPred function. Ive been
working
> with a nonlinear mixed model with no problems so far. However, when the
> parameters of the model are specified in terms of some other covariates,
> say treatment (i.e. phi1~trt1+trt2, etc) the augPred function give me the
> following error: "Error in predict.nlme(object,
> value[1:(nrow(value)/nL),,drop=FALSE], : Levels 0,1 not allowed for trt1,
> trt2". The same model specification as well as the augPred function under
> SPlus 2000 run without problems. The second question has to deal with the
> time needed for the model to converge. It really takes a lot of time to
fit
> the model on R in relation to the time required to fit the same model on
> SPlus. I can imagine this is related to the optimization algorithm or
> something like that, but I would like to have a different opinion on
these
> two issues.
>
> Thanks in advance
>
> Christian Mora
>
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