thank you for your reply - it crossed my reply to Matthew, so I’ll
by saying that my question “why does Ed Borasky” like R is now answered
a very informative way.
I am a mathematician myself, and I’ll agree that in the field of
I am working in, there’s a lot of statistics, and of course I knew of R
statistics, and i like it so again: no criticism of R.
My point was just that what I like about R needn’t have any connection
you like about R - otherwise there’d one important reason less maintain
For instance, I don’t agree with your point
Well, first of all, being a mathematician, I’ll make the claim that
any sufficiently large task, programming or otherwise, has some
statistics in it. :).
There’s graph theory, group theory, combinatorics ,…
If you do solving of polynomial equations in many variables, to model a
of this field, you can use Groebner bases I was talking about in my
The problem is that generically, the result you’ll get is of twice
complexity in the number of input variables, that is to say, you’ll
get to order of 2^(2^(n/2))) terms as a result, where n is the number of
variables as a worst case. This will eat up all your memory, no matter
much you have. A lot of work is going on to reduce that number , and
requires a lot of programming.
But I value your response and I’ll think about it in the near future,
back to using R.