TsallisCTEEstimator#
- class infomeasure.estimators.transfer_entropy.TsallisCTEEstimator(source, dest, *, cond=None, k: int = 4, q: float | int = None, noise_level=1e-08, 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)[source]
Bases:
BaseTsallisTEEstimator,ConditionalTransferEntropyEstimatorEstimator for the Tsallis conditional transfer entropy.
- Attributes:
- source, dest, condarray_like
The source (X), destination (Y) and conditional (Z) data used to estimate the conditional transfer entropy.
- k
int The number of nearest neighbors used in the estimation.
- q
float|int The Tsallis parameter, order or exponent. Sometimes denoted as \(q\), analogous to the Rényi parameter \(\alpha\).
- noise_level
float The standard deviation of the Gaussian noise to add to the data to avoid issues with zero distances.
- step_size
int,optional Step size between elements for the state space reconstruction.
- src_hist_len, dest_hist_len, cond_hist_len
int,optional Number of past observations to consider for the source, destination and conditional data.
- Raises:
ValueErrorIf the Tsallis parameter is not a positive number.
ValueErrorIf the number of nearest neighbors is not a positive integer.
ValueErrorIf the step_size is not a non-negative integer.
Notes
In the $q to 1$ limit, the Jackson sum (q-additivity) reduces to ordinary summation, and the Tallis entropy reduces to Shannon Entropy. This class of entropy measure is in particularly useful in the study in connection with long-range correlated systems and with non-equilibrium phenomena.