Ordinal pattern-based change point detection

Annika Betken (), Giorgio Micali () and Johannes Schmidt-Hieber ()
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Annika Betken: University of Twente, Department of Applied Mathematics
Giorgio Micali: University of Twente, Department of Applied Mathematics
Johannes Schmidt-Hieber: University of Twente, Department of Applied Mathematics

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2025, vol. 34, issue 4, No 4, 927-980

Abstract: Abstract The ordinal patterns of a fixed number of consecutive values in a time series are the spatial ordering of these values. Counting how often a specific ordinal pattern occurs in a time series provides important insights into the properties of the time series. In this work, we prove the asymptotic normality of the relative frequency of ordinal patterns for time series with linear increments. Moreover, we apply ordinal patterns to detect changes in the distribution of a time series.

Keywords: Ordinal patterns; Turning rate; Change point detection (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11749-025-00983-9

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