statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_beta2

statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_beta2(x, sample, bw)

Beta kernel for cdf estimation with boundary correction

Parameters:

xfloat or array_like

Points at which the kernel is evaluated. x can be scalar or 1-dim.

samplearray_like

1-d sample from which the kernel estimate is computed.

bwfloat

Bandwidth parameter, there is currently no default value for it.

Returns:

ndarray

Kernel values evaluated at x for each point in sample.

References

[1]

Bouezmarni, Taoufik, and Olivier Scaillet. 2005. “Consistency of Asymmetric Kernel Density Estimators and Smoothed Histograms with Application to Income Data.” Econometric Theory 21 (2): 390-412.

[2]

Chen, Song Xi. 1999. “Beta Kernel Estimators for Density Functions.” Computational Statistics & Data Analysis 31 (2): 131-45. https://doi.org/10.1016/S0167-9473(99)00010-9.