statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_weibull#

statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_weibull(x, sample, bw)[source]#

Weibull kernel for cumulative distribution, cdf, estimation

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]

Mombeni, Habib Allah, B Masouri, and Mohammad Reza Akhoond. 2019. “Asymmetric Kernels for Boundary Modification in Distribution Function Estimation.” REVSTAT, 1-27.