[SciPy-user] Kernel density approximation

Zachary Pincus zpincus@stanford....
Mon Nov 5 12:58:36 CST 2007


This might be a start:
scipy.stats.kde.gaussian_kde

I use it regularly for my n-d KDE needs. I think it has all of the  
moon/stick features required.

Zach


On Nov 5, 2007, at 1:45 PM, Gael Varoquaux wrote:

> Hi,
>
> What is the recommended way to compute a kernel density  
> approximation of
> a probability distribution function given a sample data ? My  
> problem is
> two dimensional, each data element is made of a pair of numbers.
>
> I currently use an histogram2d, but I would like to use a smooth  
> kernel,
> such as a gaussian, and most important, I would like the algorithm  
> to do
> the work for me as far as choosing the bandwidth :->.
>
> And I forgot to say that the function should be fast, as it is used  
> in a
> Monte Carlo algorithm, and is called many times.
>
> Yes, I know, I want the Moon, on a stick, please :->.
>
> Thanks,
>
> Gaël
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