>> about a year ago I developed for my own purposes a routine for averaging
>> irregularly-sampled data using gaussian average.
> is this similar to Kernel Density estimation?
No. It is probably closer to radial basis function interpolation (in fact, it
almost certainly is a form of RBFs):
I checked the official terminology, it is a kernel average smoother
(in the sense of ) with special weight function exp(-(x-x0)^2/const),
operating on irregularly-spaced data in 2d.
I am not sure if that is the same as what scipy.stats.kde.gaussian_kde does,
the documentation is terse. Can I be enlightened here?