[R-sig-ME] Summarizing the fitted model takes more RAM than fitting it

[Gorjanc Gregor]

Dear lme4 developers,

I am a big fan/user of your lme4 package. Thank you very much for this package and
other R related work. I would like to report my experience that summarizing the fitted
model via summary() takes more RAM than fitting it with lmer(). I noticed this several
times. The model is quite large, but not that large. Am I doing something wrong or ...?

Bellow is an example of the model I am fitting along with the "necessary" code
to summarize the fitted model. I am currently using R 2.8.0 on MS Windows Vista on
Dell Inspiron I1520 laptop having Intel(R) Core(TM) Duo CPU T7500 @ 2.20GHz 2.20GHz
and 2046 MB of RAM. Version of lme4 is 0.999375-27 as of date 2008-09-27.

> ## Fit the model
> fit9b <- lmer(tezaroj ~ pasma + roj2 + zj2 + spol + reja + jagLM +
>                                      (1 | rejec) + (1 | hy) + (1 | hys), data=podatki)
>
> summary(fit9b)
Error: cannot allocate vector of size 130.4 Mb
In addition: There were 22 warnings (use warnings() to see them)
> warnings()
Warning messages:
1: In slot(from, what) <- slot(value, what) ... :
  Reached total allocation of 1535Mb: see help(memory.size)
>
> ## Make sure R can allocate enough memory
> memory.limit(size=1900)
>
> ## Sink the output - since correlation matrix of fixed effects hides
> sink(file="tmp.txt")
> summary(fit9b)
> sink()

## Linear mixed model fit by REML
## Formula: tezaroj ~ pasma + roj2 + zj2 + spol + reja + jagLM + (1 | rejec) +      (1 | hy) + (1 | hys)
##    Data: podatki
##     AIC    BIC logLik deviance REMLdev
##  150646 152563 -75118   149507  150236
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  hys      (Intercept) 0.057519 0.23983
##  hy       (Intercept) 0.135671 0.36834
##  rejec    (Intercept) 0.268200 0.51788
##  Residual             0.297427 0.54537
## Number of obs: 85035, groups: hys, 9653; hy, 2036; rejec, 346
...

I also tried using the following things before calling summary():
- gc() and summary();

- removing all unnecessary objects in the workspace, gc() and summary();

- saving the object, starting new instance of R, loading the object and summary();

but could still not summarize the fitted object. I am really suprised that summarising the
fitted model consumes more memory than fittng it. Am I missing something?

Lep pozdrav / With regards,
    Gregor Gorjanc
----------------------------------------------------------------------
University of Ljubljana     PhD student
Biotechnical Faculty        www: http://gregor.gorjanc.googlepages.com
Animal Science Department   blog: http://ggorjan.blogspot.com
Groblje 3                   mail: gregor.gorjanc <at> bfro.uni-lj.si
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