Detecting linear trend changes in data sequences

Hyeyoung Maeng and Piotr Fryzlewicz

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We propose TrendSegment, a methodology for detecting multiple change-points corresponding to linear trend changes in one dimensional data. A core ingredient of TrendSegment is a new Tail-Greedy Unbalanced Wavelet transform: a conditionally orthonormal, bottom-up transformation of the data through an adaptively constructed unbalanced wavelet basis, which results in a sparse representation of the data. Due to its bottom-up nature, this multiscale decomposition focuses on local features in its early stages and on global features next which enables the detection of both long and short linear trend segments at once. To reduce the computational complexity, the proposed method merges multiple regions in a single pass over the data. We show the consistency of the estimated number and locations of change-points. The practicality of our approach is demonstrated through simulations and two real data examples, involving Iceland temperature data and sea ice extent of the Arctic and the Antarctic. Our methodology is implemented in the R package trendsegmentR, available from CRAN.

Keywords: change-point detection; bottom-up algorithms; piecewise-linear signal; wavelets (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2023-06-22
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in Statistical Papers, 22, June, 2023, 16. ISSN: 0932-5026

Downloads: (external link)
http://eprints.lse.ac.uk/119280/ Open access version. (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:119280

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager (lseresearchonline@lse.ac.uk).