The "birch" and "speedglm" packages may be useful. If you have access to
a multi-core computer with additional memory you may also want to
download the "REvolution" suite.

Keep in mind that R is not designed to handle giant data sets (though
having written that, I've processed data sets of dimensions on the order
of 10000x10 in R before without too many issues). If you really want to
run robust statistical analyses on large data sets you'll need to go for
a much more robust language like SAS.

On Tue, 2010-06-29 at 01:51 -0400, Aaditya Nanduri wrote:

> Hello All.
> 
> For my HW assignment, I was given 30 stocks with minute data (date,
> time, open, close, high, low, vol) over 7 years.
> 
> So, each stock has about 610000 rows of data which makes it impossible to
> calculate z-scores for mean-reversion strategies (required for HW) for even
> one stock.
> 
> Is there any way R can read only certain lines of data?
> 
> For example, in the OU process we use increments of 60. So can R read 1:60,
> then 2:61 and so on?
> 
> I recently tried a simple regression on half the data (training set) on my
> school's computer only to watch it eat up the entire memory leaving me no
> option but to restart the computer.
> 
> The data is in .csv format if it matters.
> 
> Im an undergrad learning about the basic methods in stat arb in an informal
> setting so you may assume I have absolutely no clue about pretty much
> anything and everything.
> 
> And are there any tutorials online for using quantmod? That would be very
> helpful.
> 
> Thank you very much.
> 
> Sincerely,
> Aaditya Nanduri
> 
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> 
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