[R] A comment about R:
jwd at surewest.net
Fri Jan 6 08:37:55 CET 2006
On Thursday 05 January 2006 12:13, Achim Zeileis wrote:
> . . . snip
> Whether you find this simple or not depends on what you might want to
> have. Personally, I always find it very limiting if I've only got a switch
> to choose one or another vcov matrix when there is a multitude of vcov
> matrices in use in the literature. What if you would want to do HC3
> instead of the HC(0) that is offered by Eviews...or HC4...or HAC...or
> something bootstrapped...or...
> In my view, this is the stengths of many implementation in R: you can make
> programs very modular so that the user can easily extend the software or
> re-use it for other purposes. The price you pay for that is that it is not
> as easy to as a point-and-click software that offers some standard tools.
> Of course, both sides have advantages or disadvantages.
> . . .snip
Stata's ADO scripting language has the ability to access intermediate steps
and local variables used by various commands. These are typically held in
memory until they are purged. The difference between Stata and R is more
that Stata has been streamlined into an application, the nuts and bolts
hidden away, the rivet heads counter sunk and polished, so that unless you
really need to use them, they aren't visible. It only LOOKS like you are
constrained to the readily available results of specific commands. Stata
output will tend to look very much like the standard output one becomes
accustomed to in undergraduate stat courses.
R assumes you _will_ want access to the nuts and bolts, and don't much care
about visible rivets if the system is both accurate and functional. R is
much more a programming environment in that sense. It is an important
difference. There is going to be a continuing growth in users of R as
companies see cost savings in OS. They will often be people who happily
dragged .xls files into SPSS or SPSS for analysis and then printed the
resulting reports. (Personally, I became a strong believer in statistical
analysis packages after receiving a _negative_ variance in Excel once upon a
time. I don't see how that could even be possible, but apparently it was a
known issue. Some ad hoc experimentation then demonstrated that no
spreadsheet was all that precise).
One place where R and Stata have a great deal in common is in the manner in
which graphs and charts are formatted. Stata is perhaps slightly less
bizantine, but only slightly. Both systems emphasize flexibility and quality
graphics at the price of learning to know what you are doing. That said, you
can still do a lot more with R in some areas than Stata, especially in
spatial graphics and analysis.
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