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Testing separability for continuous functional data

Published in arXiv (Cornell University) • Jan 11, 2023
NobleIDNI8P18W43R80S84
Authors:
Holger Dette
,
Gauthier Dierickx
,
Tim Kutta

Abstract

Analyzing the covariance structure of data is a fundamental task of statistics. While this task is simple for low-dimensional observations, it becomes challenging for more intricate objects, such as multivariate functions. Here, the covariance can be so complex that just saving a non-parametric esti...

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