On 1/28/2019 5:17 PM, Bert Gunter wrote:
I would say your question is foolish -- you disagree no doubt! --
because the point of using R (or Octave or C++) is to take advantage of
the packages (= "libraries" in some languages; a library is something
different in R) it (or they) offers to simplify your task. Many of R's
libraries are written in C (or Fortran) an thus **are** fast as well as
having task-appropriate functionality and UI's .
Yes, I'm well aware of the libraries in Octave. But so far as I was able
to see, none of them fit my needs. I used Octave at first because I'm
familiar with it. But far from an expert.
So I think instead of pursuing this discussion you would do well to
search. I find rseek.org <http://rseek.org> to be especially good for
this sort of thing. Searching there on "demography" brought up what
appeared to be many appropriate hits -- including the "demography"
package! -- which you could then examine to see whether and to what
extent they provide the functionality you seek.
I looked over the demography package, and it indeed appears to do what I
want. But it seems to be far more complicated than my simple problem,
and has a large learning curve.
Alan
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Jan 28, 2019 at 4:00 PM Alan Feuerbacher <alan...@comcast.net
<mailto:alan...@comcast.net>> wrote:
On 1/28/2019 4:20 PM, Rolf Turner wrote:
>
> On 1/29/19 10:05 AM, Alan Feuerbacher wrote:
>
>> Hi,
>>
>> I recently learned of the existence of R through a physicist friend
>> who uses it in his research. I've used Octave for a decade, and
C for
>> 35 years, but would like to learn R. These all have advantages and
>> disadvantages for certain tasks, but as I'm new to R I hardly
know how
>> to evaluate them. Any suggestions?
>
> * C is fast, but with a syntax that is (to my mind) virtually
> incomprehensible. (You probably think differently about this.)
I've been doing it long enough that I have little problem with it,
except for pointers. :-)
> * In C, you essentially have to roll your own for all tasks; in R,
> practically anything (well ...) that you want to do has already
> been programmed up. CRAN is a wonderful resource, and there's
more
> on github.
>
> * The syntax of R meshes beautifully with *my* thought patterns;
YMMV.
>
> * Why not just bog in and try R out? It's free, it's readily
available,
> and there are a number of good online tutorials.
I just installed R on my Linux Fedora system, so I'll do that.
I wonder if you'd care to comment on my little project that prompted
this? As part of another project, I wanted to model population growth
starting from a handful of starting individuals. This is exponential in
the long run, of course, but I wanted to see how a few basic parameters
affected the outcome. Using Octave, I modeled a single person as a
"cell", which in Octave has a good deal of overhead. The program
basically looped over the entire population, and updated each person
according to the parameters, which included random statistical
variations. So when the total population reached, say 10,000, and an
update time of 1 day, the program had to execute 10,000 x 365 update
operations for each year of growth. For large populations, say 100,000,
the program did not return even after 24 hours of run time.
So I switched to C, and used its "struct" declaration and an array of
structs to model the population. This allowed the program to
complete in
under a minute as opposed to 24 hours+. So in line with your
comments, C
is far more efficient than Octave.
How do you think R would fare in this simulation?
Alan
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