[SciPy-user] KDE question

[Robert Kern]

David Cournapeau wrote:

> For kernel estimators, you assume each component is the same 'shape', (I 
> mean same covariance matrix) right ?

This is the only form that has been implemented, yes. Fancier implementations
can adapt the covariance matrix (in KDE jargon, "bandwidth") of the kernels to
take into account the properties of the local neighborhood. However, this is
usually only done in 1-D because N-D sorting is hard.

> Maybe this make the computation 
> feasible (find all the points such as sum_i{a_i f(x - \mu_i)} = cst) ?

That boils down to evaluating on the grid again, I think.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
 that is made terrible by our own mad attempt to interpret it as though it had
 an underlying truth."
  -- Umberto Eco