Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series
The focus of this paper is an information theoretic-symbolic logic approach to extract information from complex economic systems and unlock its dynamic content. Permutation Entropy (PE) is used to capture the permutation patterns-ordinal relations among the individual values of a given time series;...
Main Authors: | Miguel Henry, George Judge |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-03-01
|
Series: | Econometrics |
Subjects: | |
Online Access: | http://www.mdpi.com/2225-1146/7/1/10 |
Similar Items
-
Implications of the Cressie-Read Family of Additive Divergences for Information Recovery
by: George G. Judge, et al.
Published: (2012-12-01) -
Evaluating Temporal Correlations in Time Series Using Permutation Entropy, Ordinal Probabilities and Machine Learning
by: Bruno R. R. Boaretto, et al.
Published: (2021-08-01) -
Entropy-based China income distributions and inequality measures
by: Fu, Q., et al.
Published: (2019) -
Quantifying the Nonlinear Dynamic Behavior of the DC-DC Converter via Permutation Entropy
by: Zhenxiong Luo, et al.
Published: (2018-10-01) -
Application of Permutation Entropy and Permutation Min-Entropy in Multiple Emotional States Analysis of RRI Time Series
by: Yirong Xia, et al.
Published: (2018-02-01)