Uncovering Discrete Non-Linear Dependence with Information Theory
In this paper, we model discrete time series as discrete Markov processes of arbitrary order and derive the approximate distribution of the Kullback-Leibler divergence between a known transition probability matrix and its sample estimate. We introduce two new information-theoretic measurements: info...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-04-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1099-4300/17/5/2606 |