[R] Reasons to Use R

Wilfred Zegwaard wilfred.zegwaard at gmail.com
Fri Apr 6 21:31:48 CEST 2007

Dear Lorenzo and Steven,

I'm not a programmer, but I have the experience that R is good for
processing large datasets, especially in combination with specialised
statistics. There are some limits to that, but R handles large datasets
/ complicated computation a lot better that SPSS for example. I cannot
speak of Fortran, but I have the experience of Pascal. I prefer R,
because in Pascal you become easily confused an endless programming
effort which has nothing to do with the problem. I do like Pascal, it's
the only programming language I actually learned, but it isn't an
adequate replacement of R.
The experience I have is that the SPSS language, and menu-driven
package, is far easier to handle than R, but when it comes to specific
computations, SPSS loses it, by far. Non-parametrics is good in R, e.g.
Dataset handling is adequate (my SPSS ports can be read), I noticed that
R has good numerical routines like optimisation (even mixed integer
programming), good procedures for regression (GLM, which is not an SPSS
standard). Try to compute a Kendall-W statistic in SPSS. It's relatively
easy in R.
The only thing that I DON'T like about R is dataset computations and
it's syntax. When I have a dataset with only non-parametric content
which is also "dirty" (dataset is incomplete / wrong value), I have to
call in almost a technician how to do that. To be honest: I use a
spreadsheet for these dataset computations, and then export it to R. But
I noted in R there are several solutions for that. With SciViews I could
get a basic feeling for it.
Pascal is basically the only programming language that I syntactically
understood. It had a kind of logical mathematical structure to it. The
logic of Fortran (and to some extent R): I completely miss it.

Statistically: R is my choice, and luckely most procedures in R are
easily accessible. And my experience with computations in R are... good.

I have done in the past simulations, especially with time-series, but I
cannot recommend R for it (arima.sim is not sufficient for these types
of simulations). I still would prefer Pascal for it. There is also an
excellent open source package for Pascal: Free Pascal, but I hardly use
it. I do have some good experiences with computations in C, but little
experience. Instead of C I would prefer R, I believe.



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