[R-sig-ME] Large data set and mixed models

Douglas Bates bates at stat.wisc.edu
Fri Oct 17 17:15:20 CEST 2008


On Fri, Oct 17, 2008 at 8:34 AM, Rense Nieuwenhuis
<rense.nieuwenhuis at me.com> wrote:
> Dear Michael,

> perhaps you could send more details about the model you're trying to
> estimate, so we could be of help.

> i.e.:
> - What is the model specification
> - What happens -> error message, uninterpretable findings?
> - A closer description of the data
> - What system are you trying to estimate this model with?

> In general I wouldn't say the 100000 cases is 'huge' in terms of R-Project.
> Sure, some models will take some time to converge, but it should be doable.

Agreed.  The largest example that I have fit with lme4 in R has about
1.7 million observations and over 60,000 non-nested random effects.

> If you'd send me (a sample of) your data, I'd be willing to take a look at
> it.

A good start would be if Michael could show us a transcript of his
attempt to fit the model he want in R, including the output from

sessionInfo()

so we know the versions of all packages being used.

> On 17-okt-2008, at 15:02, Michael Beaulieu wrote:
>
>> I would like two compare the diving behaviour of two groups of penguins (7
>> penguin in each group). Each penguin performed several dives within several
>> foraging trips. As a result, I got a huge data set of dives (nearly 100000).
>> To compare the diving behaviour of the two groups, I used a mixed model
>> with:
>> -the penguin as a random factor,
>> -the number of dives nested in the foraging trip as a repeated factor,
>> -the group, the foraging trip and maximal depth as fixed factors.
>> Covariance structure was auto-regressive.
>> I tried this model on SPSS, SAS and R but all failed.
>>
>> Has anybody been faced with such a huge dataset analysed with mixed
>> models?
>>
>> Thank you
>>
>> MiKL
>>
>> _______________________________________________
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>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
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