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Main Authors: Ruiz-Medina, M. D., Torres-Signes, A.
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2505.05168
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author Ruiz-Medina, M. D.
Torres-Signes, A.
author_facet Ruiz-Medina, M. D.
Torres-Signes, A.
contents Under mild conditions, this paper derives a least-squares local linear Fréchet curve predictor for response and regressor evaluated in a separable Hilbert space. We obtain the conditions allowing the implementation of this local linear Fréchet functional predictor in the ambient L^{2}-space of vector functions, with values in the time-varying tangent space on a compact Riemannian manifold. An intrinsic local linear Fréchet curve predictor evaluated in such a manifold is secondly proposed, based on a weighted Fréchet mean approach. Its asymptotical optimality is proved. The simulation study and real-data application analyze the finite-sample performance of the empirical versions of both predictors, compared with a geodesic Nadaraya-Watson-type curve predictor. In the real-data application, the functional prediction of the time-varying spherical coordinates of the Earth's magnetic field is addressed, from the observation of the geocentric latitude and longitude of the satellite NASA's MAGSAT spacecraft.
format Preprint
id arxiv_https___arxiv_org_abs_2505_05168
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Dynamical local Fréchet curve regression in manifolds
Ruiz-Medina, M. D.
Torres-Signes, A.
Statistics Theory
Machine Learning
Under mild conditions, this paper derives a least-squares local linear Fréchet curve predictor for response and regressor evaluated in a separable Hilbert space. We obtain the conditions allowing the implementation of this local linear Fréchet functional predictor in the ambient L^{2}-space of vector functions, with values in the time-varying tangent space on a compact Riemannian manifold. An intrinsic local linear Fréchet curve predictor evaluated in such a manifold is secondly proposed, based on a weighted Fréchet mean approach. Its asymptotical optimality is proved. The simulation study and real-data application analyze the finite-sample performance of the empirical versions of both predictors, compared with a geodesic Nadaraya-Watson-type curve predictor. In the real-data application, the functional prediction of the time-varying spherical coordinates of the Earth's magnetic field is addressed, from the observation of the geocentric latitude and longitude of the satellite NASA's MAGSAT spacecraft.
title Dynamical local Fréchet curve regression in manifolds
topic Statistics Theory
Machine Learning
url https://arxiv.org/abs/2505.05168