Measuring dispersion and serial dependence in ordinal time series based on the cumulative paired ฯ-entropy
Publication date
2021-12-26
Document type
Forschungsartikel
Author
Organisational unit
Publisher
MDPI
Series or journal
Entropy
ISSN
Periodical volume
24
Periodical issue
1
Article ID
42
Peer-reviewed
โ
Part of the university bibliography
โ
Language
English
Keyword
Cohenโs ๐
Dispersion
Ordinal time series
Serial dependence
Abstract
The family of cumulative paired ๐-entropies offers a wide variety of ordinal dispersion measures, covering many well-known dispersion measures as a special case. After a comprehensive analysis of this family of entropies, we consider the corresponding sample versions and derive their asymptotic distributions for stationary ordinal time series data. Based on an investigation of their asymptotic bias, we propose a family of signed serial dependence measures, which can be understood as weighted types of Cohenโs ๐
, with the weights being related to the actual choice of ๐. Again, the asymptotic distribution of the corresponding sample ๐
_{๐} is derived and applied to test for serial dependence in ordinal time series. Using numerical computations and simulations, the practical relevance of the dispersion and dependence measures is investigated. We conclude with an environmental data example, where the novel ๐-entropy-related measures are applied to an ordinal time series on the daily level of air quality.
Description
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Cite as
Weiร, C.H. Measuring Dispersion and Serial Dependence in Ordinal Time Series Based on the Cumulative Paired ฯ-Entropy. Entropy 2022, 24, 42. https://doi.org/10.3390/e24010042
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Published version
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