KernelTEEstimator

class infomeasure.estimators.transfer_entropy.KernelTEEstimator(source, dest, *, cond=None, bandwidth: float | int = None, kernel: str = None, prop_time: int = 0, step_size: int = 1, src_hist_len: int = 1, dest_hist_len: int = 1, cond_hist_len: int = 1, workers: int = 1, offset: int = None, base: int | float | str = 'e', **kwargs)

Bases: BaseKernelTEEstimator, TransferEntropyEstimator

Estimator for transfer entropy using Kernel Density Estimation (KDE).

Attributes:

source, destarray_like

The source (X) and destination (Y) data used to estimate the transfer entropy.

bandwidthfloat | int

The bandwidth for the kernel.

kernelstr

Type of kernel to use, compatible with the KDE implementation kde_probability_density_function().

prop_timeint, optional

Number of positions to shift the data arrays relative to each other (multiple of step_size). Delay/lag/shift between the variables, representing propagation time. Assumed time taken by info to transfer from source to destination. Alternatively called offset.

step_sizeint

Step size between elements for the state space reconstruction.

src_hist_len, dest_hist_lenint

Number of past observations to consider for the source and destination data.

Notes

A small bandwidth can lead to under-sampling, while a large bandwidth may over-smooth the data, obscuring details.