Convergence of persistence diagrams for discrete time stationary processes

Fuente: arXiv
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Main Author: Thomas, Andrew M.
Format: Preprint
Published: 2024
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author Thomas, Andrew M.
author_facet Thomas, Andrew M.
contents In this article we establish two fundamental results for the sublevel set persistent homology for stationary processes indexed by the positive integers. The first is a strong law of large numbers for the persistence diagram (treated as a measure "above the diagonal" in the extended plane) evaluated on a large class of sets and functions, beyond continuous functions with compact support. We prove this result subject to only minor conditions that the sequence is ergodic and the tails of the marginals are not too heavy. The second result is a central limit theorem for the persistence diagram evaluated on the class of all step functions; this result holds as long as a $ρ$-mixing criterion is satisfied and the distributions of the partial maxima do not decay too slowly. Our results greatly expand those extant in the literature to allow for more fruitful use in statistical applications, beyond idealized settings. Examples of distributions and functions for which the limit theory holds are provided throughout.
format Preprint
id arxiv_https___arxiv_org_abs_2407_07326
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence of persistence diagrams for discrete time stationary processes
Thomas, Andrew M.
Probability
60G10, 55N31, 60F05, 60F15
In this article we establish two fundamental results for the sublevel set persistent homology for stationary processes indexed by the positive integers. The first is a strong law of large numbers for the persistence diagram (treated as a measure "above the diagonal" in the extended plane) evaluated on a large class of sets and functions, beyond continuous functions with compact support. We prove this result subject to only minor conditions that the sequence is ergodic and the tails of the marginals are not too heavy. The second result is a central limit theorem for the persistence diagram evaluated on the class of all step functions; this result holds as long as a $ρ$-mixing criterion is satisfied and the distributions of the partial maxima do not decay too slowly. Our results greatly expand those extant in the literature to allow for more fruitful use in statistical applications, beyond idealized settings. Examples of distributions and functions for which the limit theory holds are provided throughout.
title Convergence of persistence diagrams for discrete time stationary processes
topic Probability
60G10, 55N31, 60F05, 60F15
url https://arxiv.org/abs/2407.07326