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| Format: | Artículo Open Access |
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Wiley
2024
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| Online Access: | https://onlinelibrary.wiley.com/doi/10.1002/sta4.70021 |
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| _version_ | 1867009733366382593 |
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| author | Lydia Kakampakou Emma S. Simpson Jennifer L. Wadsworth |
| author_facet | Lydia Kakampakou Emma S. Simpson Jennifer L. Wadsworth Lydia Kakampakou Emma S. Simpson Jennifer L. Wadsworth |
| collection | Wiley Open Access |
| contents | Spatial Extremal Modelling: A Case Study on the Interplay Between Margins and Dependence Lydia Kakampakou Emma S. Simpson Jennifer L. Wadsworth Stat ABSTRACT It is no secret that statistical modelling often involves making simplifying assumptions when attempting to study complex stochastic phenomena. Spatial modelling of extreme values is no exception, with one of the most common such assumptions being stationarity in the marginal and/or dependence features. If non‐stationarity has been detected in the marginal distributions, it is tempting to try to model this while assuming stationarity in the dependence, without necessarily putting this latter assumption through thorough testing. However, margins and dependence are often intricately connected and the detection of non‐stationarity in one feature might affect the detection of non‐stationarity in the other. This work is an in‐depth case study of this interrelationship, with a particular focus on a spatio‐temporal environmental application exhibiting well‐documented marginal non‐stationarity. Specifically, we compare and contrast four different marginal detrending approaches in terms of our post‐detrending ability to detect temporal non‐stationarity in the spatial extremal dependence structure of a sea surface temperature dataset from the Red Sea. 10.1002/sta4.70021 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1002/sta4.70021 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_sta4_70021 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2024 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Spatial Extremal Modelling: A Case Study on the Interplay Between Margins and Dependence Lydia Kakampakou Emma S. Simpson Jennifer L. Wadsworth Stat Spatial Extremal Modelling: A Case Study on the Interplay Between Margins and Dependence Lydia Kakampakou Emma S. Simpson Jennifer L. Wadsworth Stat ABSTRACT It is no secret that statistical modelling often involves making simplifying assumptions when attempting to study complex stochastic phenomena. Spatial modelling of extreme values is no exception, with one of the most common such assumptions being stationarity in the marginal and/or dependence features. If non‐stationarity has been detected in the marginal distributions, it is tempting to try to model this while assuming stationarity in the dependence, without necessarily putting this latter assumption through thorough testing. However, margins and dependence are often intricately connected and the detection of non‐stationarity in one feature might affect the detection of non‐stationarity in the other. This work is an in‐depth case study of this interrelationship, with a particular focus on a spatio‐temporal environmental application exhibiting well‐documented marginal non‐stationarity. Specifically, we compare and contrast four different marginal detrending approaches in terms of our post‐detrending ability to detect temporal non‐stationarity in the spatial extremal dependence structure of a sea surface temperature dataset from the Red Sea. 10.1002/sta4.70021 http://creativecommons.org/licenses/by/4.0/ |
| title | Spatial Extremal Modelling: A Case Study on the Interplay Between Margins and Dependence |
| topic | Stat |
| url | https://onlinelibrary.wiley.com/doi/10.1002/sta4.70021 |