[R-sig-ME] New version of lme4 - memory error
Andrew Robinson
A.Robinson at ms.unimelb.edu.au
Sat Jan 27 00:27:14 CET 2007
Hi Doug,
sorry, it's me having problems again :(
I can install and load the new lme4 package with no trouble, but when
I try to run the examples, I get:
> require(lme4)
Loading required package: lme4
Loading required package: Matrix
Loading required package: lattice
[1] TRUE
> sessionInfo()
R version 2.4.1 Patched (2007-01-25 r40572)
i386-unknown-freebsd6.1
locale:
C
attached base packages:
[1] "stats" "graphics" "grDevices" "utils" "datasets"
"methods"
[7] "base"
other attached packages:
lme4 Matrix lattice
"0.9975-11" "0.9975-8" "0.14-16"
> fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
> fm1 <- lmer2(Reaction ~ Days + (Days|Subject), sleepstudy)
Error in as.double(start) : Calloc could not allocate (169499040 of 4)
memory
Does anyone else find this? Please let me know what else I can do to
help.
Cheers,
Andrew
On Thu, Jan 25, 2007 at 05:12:00PM -0600, Douglas Bates wrote:
> Version 0.9975-11 of the lme4 package has been uploaded to CRAN. The
> source package should be available on the mirrors in a day or two and
> binary packages should follow soon after.
>
> There are several changes in this release of the package. The most
> important is the availability of a development version of lmer called,
> for the time being, lmer2. At present lmer2 only fits linear mixed
> models. Generalized linear mixed models will be added "soon".
> Furthermore there is no mcmcsamp method for a model fit by lmer2.
> This deficiency will also be rectified "soon". Once I have all the
> capabilities and methods currently available for lmer also available
> for the new representation I will remove the old representation and
> rename lmer2 as lmer.
>
> The current version of lmer will continue to be available throughout
> the migration process. You don't have to change anything about your
> use of that function unless you want to try the new one. It would be
> a good idea, however, to save the data and the call to lmer in
> addition to saving an lmer object, if you so choose, so that you can
> recreate the fitted model when the development version becomes the
> release version.
>
> The package contains a vignette giving the details of the new implementation.
>
> The reason I am releasing a development version in parallel with the
> production version is because I would like feedback from useR's
> regarding the development version. In my experience, testing it
> myself and with colleagues whom I visited recently, I have found that
> lmer2 is faster and more reliable than the current lmer. In
> particular, on some difficult model fits I have been able to get
> substantially better parameter estimates (i.e. the deviance at the
> lmer2 estimates is perhaps 4 or 5 lower than that at the lmer
> estimates) with lmer2 than I could with lmer.
>
> If you have fit a linear mixed model using lmer and are willing to try
> it with lmer2 I would appreciate your telling me if the parameter
> estimates are comparable and which fit was faster (use system.time()
> to check). I'm primarily interested in models fit to large data sets
> or "difficult" fits.
>
> We have established a new mailing list, R-SIG-mixed-models, for
> discussion of R software to fit mixed-effects models, especially lmer.
> See https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models for
> information or to subscribe.
>
> I know that I have said this before but this is the last time that I
> am going to change the underlying representation. Really - trust me -
> this is the last time. My theory of software development is expressed
> in a line from an old blues song, "you just keep doing it wrong till
> you do it right". I'm convinced that this time I have it right. That
> statement sounds like "famous last words", doesn't it? :-)
>
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--
Andrew Robinson
Department of Mathematics and Statistics Tel: +61-3-8344-9763
University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599
http://www.ms.unimelb.edu.au/~andrewpr
http://blogs.mbs.edu/fishing-in-the-bay/
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