[SciPy-User] Epanechnikov kernel

josef.pktd@gmai... josef.pktd@gmai...
Sat Jan 19 07:40:42 CST 2013


On Sat, Jan 19, 2013 at 8:32 AM, Skipper Seabold <jsseabold@gmail.com> wrote:
> On Sat, Jan 19, 2013 at 7:49 AM,  <josef.pktd@gmail.com> wrote:
>> On Sat, Jan 19, 2013 at 6:34 AM, francescoboccacci@libero.it
>> <francescoboccacci@libero.it> wrote:
>>> Hi all,
>>>
>>> I have a question for you. Is it possible in scipy using a Epanechnikov
>>> kernel function?
>>>
>>> I checked on scipy documentation but i found that the only way to calculate
>>> kernel-density estimate is possible only with using Gaussian kernels?
>>>
>>> Is it true?
>>
>> Yes, kde in scipy.stats only has gaussian_kde
>>
>> Also in statsmodels currently only gaussian is supported for
>> continuous data
>> http://statsmodels.sourceforge.net/devel/nonparametric.html
>> (It was removed because in the references only the bandwidth selection
>> made much difference in the estimation, but not the shape of the
>> kernel. Other kernels for continuous variables will come back
>> eventually.
>
> If you're interested in univariate KDE, then we do have the Epanechnikov kernel.
>
> http://statsmodels.sourceforge.net/devel/generated/statsmodels.nonparametric.kde.KDEUnivariate.fit.html#statsmodels.nonparametric.kde.KDEUnivariate.fit

oops, I was only looking at the fft part.

I stand corrected.
Josef

>
> Skipper
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