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Detecting changes in mixed-sampling rate data sequences

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Article numbere2762
<mark>Journal publication date</mark>28/02/2023
Issue number1
Number of pages15
Publication StatusPublished
Early online date26/09/22
<mark>Original language</mark>English


Different environmental variables are often monitored using different sampling rates; examples include half-hourly weather station measurements, daily (Formula presented.) data, and six-day satellite data. Further when researchers want to combine the data into a single analysis this often requires data aggregation or down-scaling. When one is seeking to identify changes within multivariate data, the aggregation and/or down-scaling processes obscure the changes we seek. In this article, we propose a novel changepoint detection algorithm which can analyze multiple time series for co-occurring changepoints with potentially different sampling rates, without requiring preprocessing to a standard sampling scale. We demonstrate the algorithm on synthetic data before providing an example identifying simultaneous changes in multiple variables at a location on the Greenland ice sheet using synthetic aperture radar and weather station data.