[SciPy-Dev] Splines

[Nathaniel Smith]

On 21 Feb 2013 13:51, <josef.pktd at gmail.com> wrote:
>
> On Thu, Feb 21, 2013 at 8:47 AM, Charles R Harris
> <charlesr.harris at gmail.com> wrote:
> >
> >
> > On Thu, Feb 21, 2013 at 2:54 AM, Nathaniel Smith <njs at pobox.com> wrote:
> >>
> >> I'm not an expert on spline implementation in general, but for
statistical
> >> regression applications, we need to be able to evaluate the individual
> >> functions in an arbitrary spline basis at irregular x points, which is
not
> >> well supported by the current API. (splev only computes linear
combinations
> >> of the full basis set, so to get individual basis functions we have to
do
> >> multiple evaluations with linear combinations like [0, 0, 1].) So
keeping
> >> this use case in mind would be nice :-).
> >
> > <snip>
> >
> > Can you be more specific here? Design matrices?
>
> The spline analog of np.vander.
>
> Once we have the basis function as a design matrix, we can use all the
> regular tools for linear model estimation (statsmodels).
> number of knots usually considerably smaller than number of
> observations for penalized or smoothing splines.
>
> That's what I see, and Nathaniel might have in mind.

Yes, that's what I meant.

Bonus points if we can easily get compatible implementations of R's bs()
and ns(). (bs() is trivial, we already have it, just inconveniently; I'm
pretty sure ns() is the same thing with those linear boundary conditions
someone else mentioned up-thread.)

-n
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