[R] nlme in R v.2.2.1 and S-Plus v. 7.0

Spencer Graves spencer.graves at pdf.com
Fri Jan 27 03:34:22 CET 2006


	  I see you got an error message from R.  Did you have both either the 
lme4 or the Matrix packages in the search path at the same time you ran 
nlme to get the result you got below?  If yes, please rerun with only 
nlme in the search path.  (This may not be necessary, but I always quite 
R and restart whenever I want to switch between nlme and lme4.)

	  If this is not the problem, I would encourage you to experient with 
smaller models and data sets to try to find the simplest "toy example" 
that still produces the error message you got from summary(nlme(...)), 
then submit that to this listserve.  I routinely copy reproducible 
examples into R to see if I get the same error message.  Whether I do or 
not, I think my comments are much more likely to be helpful than if I 
have to guess.  And if I'm guessing about an error message I can't 
generate myself at will, my comments may not be very helpful.

	  Regarding whether to use S-Plus 7 or R 2.2.1 for this problem, if R 
gives you an error message when S-Plus does not, doesn't that answer 
your question?  Moreover, the S-Plus logLik is higher than for R, which 
suggests that it must get closer to the actual maximum of the likelihood 
function.

	  If you'd like more help from this listserve, I suggest you PLEASE do 
read the posting guide! "www.R-project.org/posting-guide.html".  Doing 
so will on average tend to increase the speed and utility of comments 
you might receive, I believe.

	  hope this helps,
	  spencer graves

Paolo Ghisletta wrote:

> Dear R-Users,
> 
> I am comparing the nlme package in S-Plus (v. 7.0) and R (v. 2.2.1, nlme 
> package version 3.1-68.1; the lattice, Matrix, and lme4 have also just 
> been updated today, Jan. 23, 2006) on a PC (2.40 GHz Pentium 4 processor 
> and 1 GHz RAM) operating on Windows XP. I am using a real data set with 
> 1,191 units with at most 4 repeated measures per unit (data are 
> incomplete, unbalanced). I use the same code with the same starting 
> values for both programs and obtain slightly different results. I am 
> aware that at this stage my model is far from being well specified for 
> the given data. Nevertheless, I wonder whether one program is more 
> suited than the other to pursue my modeling.
> 
> Below I included the input + output code, first for S-Plus, than for R.
> 
> Many thanks and best regards,
> Paolo Ghisletta
> 
> ############
> #S-Plus
> #min=4, max=41
>  > logistic4.a <- nlme(jugs ~ 4 + 41 / (1 + xmid*exp( -scal*I(occ-1) + 
> u)), fixed=scal+xmid~1, random= u~1 |id, start=c(scal=.2, xmid=155), 
> data=jug, na.action=na.exclude, method="ML")
>  > summary(logistic4.a)
> Nonlinear mixed-effects model fit by maximum likelihood
>   Model: jugs ~ 4 + 41/(1 + xmid * exp( - scal * I(occ - 1) + u))
>  Data: jug
>        AIC     BIC    logLik
>   29595.62 29621.3 -14793.81
> 
> Random effects:
>  Formula: u ~ 1 | id
>                u Residual
> StdDev: 5.162391 3.718887
> 
> Fixed effects: scal + xmid ~ 1
>         Value Std.Error   DF  t-value p-value
> scal   4.9697    0.0823 3339 60.39508  <.0001
> xmid 683.5634  125.8509 3339  5.43153  <.0001
> 
> Standardized Within-Group Residuals:
>        Min         Q1          Med        Q3      Max
>  -10.66576 -0.5039498 0.0002772166 0.1226745 5.453209
> 
> Number of Observations: 4531
> Number of Groups: 1191
> 
> ############
> # R
>  > #min=4, max=41
>  > logistic4.a <- nlme(jugs ~ 4 + 41 / (1 + xmid*exp( -scal*I(occ-1)+ 
> u)), data=jug, fixed=scal+xmid~1, random= u~1 |id, start=c(scal=.2, 
> xmid=155), method="ML", na.action=na.exclude)
>  > summary(logistic4.a)
> Nonlinear mixed-effects model fit by maximum likelihood
>   Model: jugs ~ 4 + 41/(1 + xmid * exp(-scal * I(occ - 1) + u))
>  Data: jug
>        AIC      BIC    logLik
>   29678.11 29703.78 -14835.05
> 
> Random effects:
>  Formula: u ~ 1 | id
>                u Residual
> StdDev: 5.116542 3.767097
> 
> Fixed effects: scal + xmid ~ 1
>         Value Std.Error   DF  t-value p-value
> scal   4.9244   0.08121 3339 60.63763       0
> xmid 633.6956 115.37512 3339  5.49248       0
> Erreur dans dim(x) : aucun slot de nom "Dim" pour cet objet de la classe 
> "correlation"
> 
> 
> 
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> 
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