{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:40:19Z","timestamp":1760236819487,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,26]],"date-time":"2021-12-26T00:00:00Z","timestamp":1640476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The family of cumulative paired \u03d5-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 Cohen\u2019s \u03ba, with the weights being related to the actual choice of \u03d5. Again, the asymptotic distribution of the corresponding sample \u03ba\u03d5 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 \u03d5-entropy-related measures are applied to an ordinal time series on the daily level of air quality.<\/jats:p>","DOI":"10.3390\/e24010042","type":"journal-article","created":{"date-parts":[[2021,12,27]],"date-time":"2021-12-27T01:00:54Z","timestamp":1640566854000},"page":"42","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Measuring Dispersion and Serial Dependence in Ordinal Time Series Based on the Cumulative Paired \u03d5-Entropy"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8739-6631","authenticated-orcid":false,"given":"Christian","family":"Wei\u00df","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, Helmut Schmidt University, 22043 Hamburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Agresti, A. 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