Extremal correlation coefficient for functional data

Abstract We propose a coefficient that measures extremal dependence in paired samples of functions. It has properties similar to the Pearson correlation, but differs in two significant ways: (i) it is designed to measure dependence between curves; and (ii) it focuses only on extreme curves. The new coefficient is derived within the framework of regular variation in Banach spaces. A consistent estimator is proposed and justified by an asymptotic analysis and a simulation study. The usefulness of the new coefficient is illustrated using financial and climate functional data.

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Publication Details

Journal
Biometrika
Published
2025-10-28
DOI
https://doi.org/10.1093/biomet/asaf077
Primary Topic
Statistical Methods and Inference
Type
article
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article

Extremal correlation coefficient for functional data

Piotr Kokoszka, M. Kim
Biometrika
Statistical Methods and Inference
article

Extremal correlation coefficient for functional data

Piotr Kokoszka, M. Kim
article en

Abstract

Abstract We propose a coefficient that measures extremal dependence in paired samples of functions. It has properties similar to the Pearson correlation, but differs in two significant ways: (i) it is designed to measure dependence between curves; and (ii) it focuses only on extreme curves. The new coefficient is derived within the framework of regular variation in Banach spaces. A consistent estimator is proposed and justified by an asymptotic analysis and a simulation study. The usefulness of the new coefficient is illustrated using financial and climate functional data.

BiometrikaVol. 113(1)
West Virginia University (US), Colorado State University (US)
Openalex Percentile: Top 70%
Statistical Methods and Inference
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