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statsmodels.nonparametric.kde.KDE

class statsmodels.nonparametric.kde.KDE(endog)[source]

Kernel Density Estimator

Parameters :

endog : array-like

The variable for which the density estimate is desired.

Notes

If cdf, sf, cumhazard, or entropy are computed, they are computed based on the definition of the kernel rather than the FFT approximation, even if the density is fit with FFT = True.

Methods

evaluate(point) Evaluate density at a single point.
fit([kernel, bw, fft, weights, gridsize, ...]) Attach the density estimate to the KDE class.

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