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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

cdf() Returns the cumulative distribution function evaluated at the support.
cumhazard() Returns the hazard function evaluated at the support.
entropy() Returns the differential entropy evaluated at the support ..
evaluate(point) Evaluate density at a single point.
fit([kernel, bw, fft, weights, gridsize, ...]) Attach the density estimate to the KDE class.
icdf() Inverse Cumulative Distribution (Quantile) Function
sf() Returns the survival function evaluated at the support.

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