statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_weibull

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

Weibull kernel for density, pdf, estimation

Based on cdf kernel by Mombeni et al. (2019)

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.