Ordinal pattern-based change point detection
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.
Authors
- Johannes Schmidt-Hieber (ORCID: https://orcid.org/0000-0003-2699-4990)
- Annika Betken
- Giorgio Micali
Institutions
- University of Twente (NL)
Publication Details
- Journal
- Test
- Published
- 2025-08-15
- DOI
- https://doi.org/10.1007/s11749-025-00983-9
- Citations
- 2
- Primary Topic
- Time Series Analysis and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 2.97
Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek