On Sep 16, 7:46 pm, Jason Grout <jason-s...@creativetrax.com> wrote:
> William Stein wrote:
> > On Wed, Sep 16, 2009 at 10:03 AM, <jason-s...@creativetrax.com> wrote:
> >> Another idea for a project is to finish the statistics module wrapping
> >> functionality in R. I'm teaching a modeling class right now and I wish I
> >> had a nice module of statistics functionality.
>
> > Thanks. If you have any more specific thoughts about this project, it
> > would be massively appreciated. Since I have an undergrad student who
> > I've hired this quarter to work a few hours a week on doing just the
> > above. Unfortunately, I personally have never taught any classes that
> > use statistics much... so if you could say more about what you might
> > want such a "nice module" to do, it would be very useful!
>
> > I've cc'd this email to sage-devel and the student (Andrew Hou), in
> > case more people want to make comments.
>
> I'm looking into updating the R and rpy packages. Right now, our R is
> way out of date. Also, rpy2 has a lower-level interface to R than rpy;
> presumably it's faster/better.
rpy2 is in fact providing 2 interfaces: a lower-level one (close to
R's C API),
and an higher-level one (written using the lower-level one, and able
to use
lower-level objects instead of higher-level ones). The lower-level
interface
is in fact design to permit the implementation of other higher-level
interfaces (rnumpy is one example).
The lower-level interface is indeed faster than R, and even more when
using "psyco".
L.
> Andrew, have you looked at updating the spkgs?
>
> Today, I could have just used the distributions and histograms/boxplots.
> Nothing fancy; just give me 1000 values from a normal distribution
> with given parameters, draw a histogram, draw the pdf, calculate the
> expected value, standard deviation, etc. The other day I could have
> used functionality to calculate the five-number summary.
>
> Scipy also does some of this stuff, but R is *much* better. For
> example, R has *nine* different quartile algorithms you can choose from
> (compared to scipy's one, and matplotlib's sort of broken one (it
> doesn't calculate quartiles between data points)). R also has the
> advantage of being vetted/used by a huge statistics community.
>
> R has a C interface for lots of functions (like the distribution
> functions that I wanted today). I imagine that a stats module would use
> Cython to call the C functions for these sorts of things, but then use
> rpy2 for the rest of the interaction with R.
>
> Jason
>
> --
> Jason Grout
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