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:
- x
floator array_like Points at which the kernel is evaluated.
xcan be scalar or 1-dim.- samplearray_like
1-d sample from which the kernel estimate is computed.
- bw
float Bandwidth parameter, there is currently no default value for it.
- x
- Returns:
ndarrayKernel 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.