Harnessing the power of topological data analysis to detect change points
Abstract We introduce a novel geometry‐oriented methodology, based on the emerging tools of topological data analysis, into the change‐point detection framework. The key rationale is that change points are likely to be associated with changes in geometry behind the data‐generating process. While the...
Published in: | Environmetrics |
---|---|
Main Authors: | , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2019
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1002/env.2612 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fenv.2612 https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2612 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/env.2612 https://onlinelibrary.wiley.com/doi/am-pdf/10.1002/env.2612 |
id |
crwiley:10.1002/env.2612 |
---|---|
record_format |
openpolar |
spelling |
crwiley:10.1002/env.2612 2024-09-15T18:23:17+00:00 Harnessing the power of topological data analysis to detect change points Islambekov, Umar Yuvaraj, Monisha Gel, Yulia R. National Science Foundation 2019 http://dx.doi.org/10.1002/env.2612 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fenv.2612 https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2612 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/env.2612 https://onlinelibrary.wiley.com/doi/am-pdf/10.1002/env.2612 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#am http://onlinelibrary.wiley.com/termsAndConditions#vor Environmetrics volume 31, issue 1 ISSN 1180-4009 1099-095X journal-article 2019 crwiley https://doi.org/10.1002/env.2612 2024-07-04T04:31:33Z Abstract We introduce a novel geometry‐oriented methodology, based on the emerging tools of topological data analysis, into the change‐point detection framework. The key rationale is that change points are likely to be associated with changes in geometry behind the data‐generating process. While the applications of topological data analysis to change‐point detection are potentially very broad, in this paper, we primarily focus on integrating topological concepts with the existing nonparametric methods for change‐point detection. In particular, the proposed new geometry‐oriented approach aims to enhance detection accuracy of distributional regime shift locations. Our simulation studies suggest that integration of topological data analysis with some existing algorithms for change‐point detection leads to consistently more accurate detection results. We illustrate our new methodology in application to the two closely related environmental time series data sets—ice phenology of the Lake Baikal and the North Atlantic Oscillation indices, in a research query for a possible association between their estimated regime shift locations. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Wiley Online Library Environmetrics 31 1 |
institution |
Open Polar |
collection |
Wiley Online Library |
op_collection_id |
crwiley |
language |
English |
description |
Abstract We introduce a novel geometry‐oriented methodology, based on the emerging tools of topological data analysis, into the change‐point detection framework. The key rationale is that change points are likely to be associated with changes in geometry behind the data‐generating process. While the applications of topological data analysis to change‐point detection are potentially very broad, in this paper, we primarily focus on integrating topological concepts with the existing nonparametric methods for change‐point detection. In particular, the proposed new geometry‐oriented approach aims to enhance detection accuracy of distributional regime shift locations. Our simulation studies suggest that integration of topological data analysis with some existing algorithms for change‐point detection leads to consistently more accurate detection results. We illustrate our new methodology in application to the two closely related environmental time series data sets—ice phenology of the Lake Baikal and the North Atlantic Oscillation indices, in a research query for a possible association between their estimated regime shift locations. |
author2 |
National Science Foundation |
format |
Article in Journal/Newspaper |
author |
Islambekov, Umar Yuvaraj, Monisha Gel, Yulia R. |
spellingShingle |
Islambekov, Umar Yuvaraj, Monisha Gel, Yulia R. Harnessing the power of topological data analysis to detect change points |
author_facet |
Islambekov, Umar Yuvaraj, Monisha Gel, Yulia R. |
author_sort |
Islambekov, Umar |
title |
Harnessing the power of topological data analysis to detect change points |
title_short |
Harnessing the power of topological data analysis to detect change points |
title_full |
Harnessing the power of topological data analysis to detect change points |
title_fullStr |
Harnessing the power of topological data analysis to detect change points |
title_full_unstemmed |
Harnessing the power of topological data analysis to detect change points |
title_sort |
harnessing the power of topological data analysis to detect change points |
publisher |
Wiley |
publishDate |
2019 |
url |
http://dx.doi.org/10.1002/env.2612 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fenv.2612 https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2612 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/env.2612 https://onlinelibrary.wiley.com/doi/am-pdf/10.1002/env.2612 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Environmetrics volume 31, issue 1 ISSN 1180-4009 1099-095X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#am http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/env.2612 |
container_title |
Environmetrics |
container_volume |
31 |
container_issue |
1 |
_version_ |
1810463476778270720 |