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Riemannian Distances between Covariance Operators and Gaussian Processes

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Functional and High-Dimensional Statistics and Related Fields (IWFOS 2020)

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

In thisworkwe study several recently formulated Riemannian distances between infinite-dimensional positive definite Hilbert-Schmidt operators in the context of covariance operators associated with functional random processes. Specifically, we focus on the affine-invariant Riemannian and Log-Hilbert-Schmidt distances and the family of Alpha Procrustes distances, which include both the Bures-Wasserstein and Log-Hilbert-Schmidt distances as special cases. In particular, we present finitedimensional approximations of the infinite-dimensional distances and show their convergence to the exact distances. The theoretical formulation is illustrated with numerical experiments on covariance operators of Gaussian processes.

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Correspondence to Minh Hà Quang .

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Quang, M.H. (2020). Riemannian Distances between Covariance Operators and Gaussian Processes. In: Aneiros, G., Horová, I., Hušková, M., Vieu, P. (eds) Functional and High-Dimensional Statistics and Related Fields. IWFOS 2020. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-47756-1_24

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