Change Point Detection for Functional Autoregressive Processes on the Sphere

Federica Spoto; Alessia Caponera; Pierpaolo Brutti

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arXiv · 2512.03255

Change Point Detection for Functional Autoregressive Processes on the Sphere

Federica Spoto·Alessia Caponera·Pierpaolo Brutti

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Abstract

We introduce a novel framework for change point detection in spherical functional autoregressive (SPHAR) processes, enabling the identification of structural breaks in spatio-temporal random fields on the sphere. Our LASSO-regularized estimator, based on penalized dynamic programming in the harmonic domain, operates without knowledge of the number or locations of change points and offers non-asymptotic theoretical guarantees. This approach provides a new tool for analyzing nonstationary phenomena on the sphere, relevant to climate science, cosmology, and beyond.

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Federica Spoto, Alessia Caponera, Pierpaolo Brutti. 2025-12-02. Change Point Detection for Functional Autoregressive Processes on the Sphere. https://arxiv.org/abs/2512.03255

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