[SciPy-User] sample from kernel density estimate

[josef.pktd at gmail.com]

On Tue, Feb 2, 2010 at 10:57 AM, Alan G Isaac <aisaac at american.edu> wrote:
>> On Tue, Feb 2, 2010 at 10:23 AM, Alan G Isaac<aisaac at american.edu>  wrote:
>>> I have a kernel density estimate from scipy.stats.gaussian_kde.
>>> What's the best way to sample from it?  (Not from the underlying data.)
>
>
> On 2/2/2010 10:31 AM, josef.pktd at gmail.com wrote:
>> I think stats.kde.gaussian_kde.resample  does it.
>> If I remember correctly, it samples from the underlying data and adds
>> a normal noise. I think I read somewhere that that is equivalent to
>> sampling from the kernel density directly.
>
>
> That appears to be correct.
> I was using the online docs,
> which did not show this method.

I added it to the list of methods in the docs.

Josef

> However, `help` does show it::
>
>         |  resample(self, size=None)
>         |      Randomly sample a dataset from the estimated pdf.
>         |
>         |      Parameters
>         |      ----------
>         |      size : int, optional
>         |          The number of samples to draw.
>         |          If not provided, then the size is the same as the underlying
>         |          dataset.
>         |
>         |      Returns
>         |      -------
>         |      dataset : (self.d, size)-array
>         |          sampled dataset
>
> Thanks,
> Alan
>
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