[R] Newbie questions
Thomas Lumley
thomas at biostat.washington.edu
Tue Oct 31 00:07:48 CET 2000
On Mon, 30 Oct 2000, Zsombor Cseres-Gergely wrote:
> Hi,
>
> I am new to R, but a fairly `old' user of Stata. I read posts asking about
> survey methods and large datasets in the archive, so I will not ask those
> questions again. But some still remain:
> - R seems to consume more memory given the same set of data, say if I have
> only a data frame defined, than Stata. Am I right if I think that this is
> because the object oriented nature of R and can not be overcome (ie., sort
> of traedoff between efficiency and complexity as with assembly <-> C <->
> C++/Java)?
Yes it is unavoidable though it isn't because of object
orientedness. Stata saves memory by allowing only one rectangular dataset
at a time, which simplifies things a lot. Stata also has a simpler
programming language.
> - If not, is it a design goal of the developers to do speed/memory
> optimization (apart from dynamic memory allocation, which, as I understand
> orthogonal to this problem)
There is ongoing speed/memory optimisation, but it's not going to make a
huge difference to most problems.
> - Since sometimes I need to use modestly really large datasets (60000*300
> matrix), I wonder if I can do that in R at all? More adequately: is R
> scalable without limits by brute force (adding more CPU/RAM)?
R is scalable up to at least 2Gb of memory (perhaps more now on 64bit
machines). It does not scale with added CPUs. Faster CPUs help, of
course.
> - Browsing the package lists, I have not seen a library for hypothesis
> testing. Everybody builds it from primitives or serious people do not do
> this at all?
library(ctest) is in the main R distribution. It has a lot of classical
hypothesis tests.
> BTW, I compiled R on the Hurd (http://hurd.gnu.org). It compiled flawlessly,
> but I was not able to test it because an X failure I have not been able to
> track down yet (X is somewhat immature in the Hurd).
It's good to hear that R works with the Hurd.
-thomas
Thomas Lumley
Assistant Professor, Biostatistics
University of Washington, Seattle
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