[R] Reasons to Use R

Wilfred Zegwaard wilfred.zegwaard at gmail.com
Mon Apr 9 03:45:03 CEST 2007

Dear Johann and Gabor,

It's what amounts to large datasets. There are hundreds of datasets R
can't handle, probably thousands or more. I noticed on my computer
(which is nothing more that an average PC) that R breaks down after 250
MB of memory. I also note that SPSS breaks down, Matlab, etc.

I'm not a SAS user, but I have worked in the past with SAS. It's very
good as a remember, but it's ten years ago. And it's a "dollar machine"
I've been told: you add dollars to SAS as you add dollars to a Porsche.
I haven't got it and for most statistical applications it isn't
necessary I've been told. R is sufficient for that. The datasets I use
are often not that big (the way I like it).
About three years ago I spoke to somebody who has worked with it and
said "it's database system is excellent and statistical profound".
Someone with a PhD, so probably he is right.

Monte-Carlo simulations are computationally time-consuming, but probably
these can be done in R. I haven't seen any libaries for it (they might
be there). It has been done with S (the commercial counterpart of R), so
probably with R too. If you tie Monte Carlo simulaton with large
datasets you probably run into problems with a conventional R system.
What I've been told in those instances is "buy a new computer" / "add
memory and buy a new processor"... and don't smoke hashiesh.

That wasn't a good advice because the guy who told me smoked hashiesh
like hell and drank Pastis (blue liqor) like water. I kicked him out.
But that's another story.



(I drink wine and tailor made beer, and only on occasions. That's why.
His simulations were good I've been told.)

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