Thu Feb 21 07:51:10 CST 2013
On Thu, Feb 21, 2013 at 8:47 AM, Charles R Harris
> On Thu, Feb 21, 2013 at 2:54 AM, Nathaniel Smith <email@example.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 :-).
> 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.
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