Symbolic transfer entropy rate is equal to transfer entropy rate for bivariate finite-alphabet stationary ergodic Markov processes

Nonlinear Sciences – Chaotic Dynamics

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6 pages, submitted to IEEE Transactions on Information Theory

Scientific paper

Transfer entropy is a measure of the magnitude and the direction of information flow between jointly distributed stochastic processes. In recent years, its permutation versions are considered in the literature to estimate the transfer entropy by counting the number of occurrence of orderings between values, not the values themselves. Here, we introduce the transfer entropy rate and its permutation version, the symbolic transfer entropy rate, and show that they are equal to each other for any bivariate finite-alphabet stationary ergodic Markov process. Our proof is based on the duality between values and orderings, which is introduced in [T. Haruna and K. Nakajima, Physica D 240, 1370 (2011)] and may give a coherent basis for the relationship between information theoretical quantities and their permutation versions defined on finite-alphabet stationary stochastic processes. We also discuss the relationship among the transfer entropy rate, the time-delayed mutual information rate and their permutation versions.

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