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Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Detecting changes in mixed-sampling rate data sequences
AU - Lowther, Aaron
AU - Killick, Rebecca
AU - Eckley, Idris
PY - 2023/2/28
Y1 - 2023/2/28
N2 - 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.
AB - 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.
KW - changepoints
KW - multi-frequency
KW - multivariate
KW - segmentation
U2 - 10.1002/env.2762
DO - 10.1002/env.2762
M3 - Journal article
VL - 34
JO - Environmetrics
JF - Environmetrics
SN - 1180-4009
IS - 1
M1 - e2762
ER -