Detecting changes in mixed-sampling rate data sequences

Lowther, Aaron and Killick, Rebecca and Eckley, Idris (2023) Detecting changes in mixed-sampling rate data sequences. Environmetrics, 34 (1): e2762. ISSN 1180-4009

Text (draft-ol-black)
draft_ol_black.pdf - Accepted Version
Available under License Creative Commons Attribution.
Download (863kB)

Abstract

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.