[SciPy-user] guassian_kde and kernel regression

[Frank Lagor]

This question is probably for Robert Kern, because I believe the he wrote
the gaussian_kde class in scipy.stats.kde, however I would very much
appreciate a response from anyone else who could help.  My question is:  Is
there currently any way to perform weighted kernel density estimation using
the gaussian_kde class?   If not, what needs to be done, and how do I get
started?

Just for clarity sake-- by weighted KDE  I mean that I have more than just
the distribution of points for the density estimate.  I also have an
associated probability with each point.  In this case, I believe it becomes
a regression problem and I think is referred to as kernel regression.  I
would very much like to use the class to perform both KDE and wKDE.

Thanks in advance,
Frank
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