[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

> - 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 Lumley
Assistant Professor, Biostatistics
University of Washington, Seattle

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