[R-sig-ME] problems with allocate memory

[cumuluss at web.de]

Hi Andrew and David,

thank you very much for your tips. Similar things were discussed in 
another posting. My first thoughts on the model-averaging approach were 
I can’t do this with this dataset. But after this discussion here I have 
to take this into account I guess. I will give it a try.
Best wishes
Paul

Am 23.12.2011 00:02, schrieb David Duffy:
> On Fri, 23 Dec 2011, Andrew Robinson wrote:
>
>> Hi Paul,
>>
>> I apologize if this has already been discussed and rejected, but I
>> also echo an earlier suggestion of Douglas's that you should think
>> about working with a sample of your data instead of all of it. ...
>> You might even try a model-averaging approach such as
>> is used in e.g. imputation; fit the model ten times to a tenth of the
>> data and average the results.
>
> And see
>
> http://www.bepress.com/harvardbiostat/paper33/
>
> "We propose a computationally efficient strategy based on the
> Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to
> collapsed versions of the data. The strategy is applied to investigate
> the relationship between ischemic heart disease, socioeconomic status
> and age/gender category in New South Wales, Australia, based on outcome
> data consisting of approximately 33 million records."
>
>