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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