statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_bs

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

Birnbaum Saunders (normal) kernel for cdf estimation.

Parameters:

• x (array_like, float) – Points for which density is evaluated. x can be scalar or 1-dim.

• sample (ndarray, 1-d) – Sample from which kde is computed.

• bw (float) – Bandwidth parameter, there is currently no default value for it.

Return type:

Components for kernel estimation

References

[1]

Jin, Xiaodong, and Janusz Kawczak. 2003. “Birnbaum-Saunders and Lognormal Kernel Estimators for Modelling Durations in High Frequency Financial Data.” Annals of Economics and Finance 4: 103–24.

[2]

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