statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_lognorm

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

Log-normal kernel for density, pdf, 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.

Notes

Warning: parameterization of bandwidth will likely be changed

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.