In message [EMAIL PROTECTED], Prof Brian
Ripley [EMAIL PROTECTED] writes
But Bert's caveats apply: you have 200 problems of size 20,000 since in
QDA each class's distribution is estimated separately, and a single pass
will give you the sufficient statistics however large the dataset is.
I
Hi,
Also I agree those cases are relatively rare in STATISTICAL analysis, you
can encounter them for simulation topics (natural catalysm a 5 meter in the
topographics can change all the simulations)
Two ideas (in addition to loading several sections) is
1- to search for duplicate cases and
In message [EMAIL PROTECTED], r-help-
[EMAIL PROTECTED] writes
Can comeone give me an example (perhaps in a private response, since I'm off
topic here) where one actually needs all cases in a large data set (large
being 1e6, say) to do a STATISTICAL analysis? By statistical I exclude,
say
On Tue, 15 Feb 2005, Graham Jones wrote:
In message [EMAIL PROTECTED], r-help-
[EMAIL PROTECTED] writes
[Actually quoting Bert Gunter, BTW]
Can comeone give me an example (perhaps in a private response, since I'm off
topic here) where one actually needs all cases in a large data set (large
being
read all 200 million rows a pipe dream no matter what
platform I'm using?
In principle R can handle this with enough memory. However,
200 million
rows and three columns is 4.8Gb of storage, and R usually needs a few
times the size of the data for working space.
You would likely be
'
Cc: r-help@stat.math.ethz.ch
Subject: Off topic -- large data sets. Was RE: [R] 64 Bit R Background
Question
read all 200 million rows a pipe dream no matter what
platform I'm using?
In principle R can handle this with enough memory. However, 200
million rows and three columns is 4.8Gb
On Mon, 14 Feb 2005, Berton Gunter wrote:
read all 200 million rows a pipe dream no matter what
platform I'm using?
In principle R can handle this with enough memory. However,
200 million
rows and three columns is 4.8Gb of storage, and R usually needs a few
times the size of the data for working
