BayesTEEstimator

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

Bases: BaseBayesTEEstimator, TransferEntropyEstimator

Estimator for the Bayes transfer entropy.

Bayesian transfer entropy estimator using Dirichlet prior with concentration parameter α. Provides principled handling of sparse data through Bayesian probability estimates.

Attributes:

source, destarray_like

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

alphafloat | str

The concentration parameter α of the Dirichlet prior. Either a float or a string specifying the choice of concentration parameter.

Kint, optional

The support size. If not provided, uses the observed support size.

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, optional

Step size between elements for the state space reconstruction.

src_hist_len, dest_hist_lenint, optional

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

See also

infomeasure.estimators.entropy.bayes.BayesEntropyEstimator

Bayesian entropy estimator with Dirichlet prior.

Notes

This estimator uses Bayesian probability estimates with a Dirichlet prior to compute transfer entropy through the entropy combination formula.

Note that the entropy combination formula is used (_generic_te_from_entropy) not a dedicated implementation as other TE might have.