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A penalised piecewise-linear model for non-stationary extreme value analysis of peaks over threshold.

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Title: A penalised piecewise-linear model for non-stationary extreme value analysis of peaks over threshold.
Authors: Barlow, Anna Maria1 (AUTHOR), Mackay, Ed1,2 (AUTHOR) e.mackay@exeter.ac.uk, Eastoe, Emma1 (AUTHOR), Jonathan, Philip1,3 (AUTHOR)
Source: Ocean Engineering. Jan2023, Vol. 267, pN.PAG-N.PAG. 1p.
Subjects: Extreme value theory
Abstract: Metocean extremes often vary systematically with covariates such as direction and season. In this work, we present non-stationary models for the size and rate of occurrence of peaks over threshold of metocean variables with respect to one- or two-dimensional covariates. The variation of model parameters with covariate is described using a piecewise-linear function in one or two dimensions, defined with respect to pre-specified node locations on the covariate domain. Parameter roughness is regulated to provide optimal predictive performance, assessed using cross-validation, within a penalised likelihood framework for inference. Parameter uncertainty is quantified using bootstrap resampling. The models are used to estimate extremes of storm-peak significant wave height with respect to direction and season for a site in the northern North Sea. A covariate representation based on a triangulation of the direction-season domain with six nodes gives good predictive performance. The penalised piecewise-linear framework provides a flexible representation of covariate effects at reasonable computational cost. • Non-stationary model for extreme values of a variable with respect to covariates. • Generalised Pareto scale and shape parameters modelled as piecewise-linear functions. • Parameter variation penalised to obtain optimal predictive performance. • Model is computationally efficient and sufficiently flexible to capture covariate effects. • Open-source software available for model fitting. [ABSTRACT FROM AUTHOR]
Copyright of Ocean Engineering is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Metocean extremes often vary systematically with covariates such as direction and season. In this work, we present non-stationary models for the size and rate of occurrence of peaks over threshold of metocean variables with respect to one- or two-dimensional covariates. The variation of model parameters with covariate is described using a piecewise-linear function in one or two dimensions, defined with respect to pre-specified node locations on the covariate domain. Parameter roughness is regulated to provide optimal predictive performance, assessed using cross-validation, within a penalised likelihood framework for inference. Parameter uncertainty is quantified using bootstrap resampling. The models are used to estimate extremes of storm-peak significant wave height with respect to direction and season for a site in the northern North Sea. A covariate representation based on a triangulation of the direction-season domain with six nodes gives good predictive performance. The penalised piecewise-linear framework provides a flexible representation of covariate effects at reasonable computational cost. • Non-stationary model for extreme values of a variable with respect to covariates. • Generalised Pareto scale and shape parameters modelled as piecewise-linear functions. • Parameter variation penalised to obtain optimal predictive performance. • Model is computationally efficient and sufficiently flexible to capture covariate effects. • Open-source software available for model fitting. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Ocean Engineering is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.oceaneng.2022.113265
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      – Code: eng
        Text: English
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      – SubjectFull: Extreme value theory
        Type: general
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      – TitleFull: A penalised piecewise-linear model for non-stationary extreme value analysis of peaks over threshold.
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            NameFull: Barlow, Anna Maria
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            NameFull: Mackay, Ed
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            NameFull: Eastoe, Emma
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              M: 01
              Text: Jan2023
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              Y: 2023
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              Value: 267
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