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# gaussian_kde_gpu
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GPU Gaussian kernel density estimation
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## GPU Gaussian kernel density estimation
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The provided function `gaussian_kde_gpu()` is a simplified version of Scipy's `gaussian_kde`. It does not support weights and only uses the default Scott's Rule for bandwidth estimation. However, it leverages the computative power of a CUDA supported GPU via Numba. Given the random variable `p` it will estimate the probability density function (PDF) at query point `q` in the following way:
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``` {.python .numberLines}
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from gaussian_kde_gpu import gaussian_kde_gpu
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density = = gaussian_kde_gpu(p, q)
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```
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For more details see [tutorial](GPU_Gaussian_kernel_density_estimation.ipynb).
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### Requirements
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- Numpy
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- Numba

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