[SciPy-Dev] Expanding Scipy's KDE functionality

[Sturla Molden]

On 24.01.2013 20:13, josef.pktd at gmail.com wrote:

> Besides the boundary problem in bounded domains, there is also the
> problem with unbounded domains, that the tails might not be well
> captured by a kde, especially with heavier tails.

Information is always lost by smoothing.

One can always use a delta function as kernel though. It retains all the 
information we have about the sampled distribution.

For unbounded domains the KDE can be seen as a censored data problem. 
One can estimate the invisible boundaries by computing BIC or MML (or by 
cross-validation).


Sturla