[SciPy-User] R: Re: Epanechnikov kernel

[francescoboccacci at libero.it]

Thanks


Francesco

>----Messaggio originale----
>Da: jsseabold at gmail.com
>Data: 19/01/2013 14.32
>A: "SciPy Users List"<scipy-user at scipy.org>
>Ogg: Re: [SciPy-User] Epanechnikov kernel
>
>On Sat, Jan 19, 2013 at 7:49 AM,  <josef.pktd at gmail.com> wrote:
>> On Sat, Jan 19, 2013 at 6:34 AM, francescoboccacci at libero.it
>> <francescoboccacci at 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
>
>Skipper
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