nonparametric.bandwidths.bw_scott()

statsmodels.nonparametric.bandwidths.bw_scott

statsmodels.nonparametric.bandwidths.bw_scott(x, kernel=None) [source]

Scott?s Rule of Thumb

Parameters:

x : array-like

Array for which to get the bandwidth

kernel : CustomKernel object

Unused

Returns:

bw : float

The estimate of the bandwidth

Notes

Returns 1.059 * A * n ** (-1/5.) where

A = min(std(x, ddof=1), IQR/1.349)
IQR = np.subtract.reduce(np.percentile(x, [75,25]))

References

Scott, D.W. (1992) Multivariate Density Estimation: Theory, Practice, and
Visualization.
doc_statsmodels
2017-01-18 16:13:02
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