Topological data analysis for random sets and its application in detecting outliers and goodness of fit testing

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Main Authors: Đogaš, Vesna Gotovac, Mandarić, Marcela
Format: Preprint
Published: 2024
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author Đogaš, Vesna Gotovac
Mandarić, Marcela
author_facet Đogaš, Vesna Gotovac
Mandarić, Marcela
contents In this paper we present the methodology for detecting outliers and testing the goodness-of-fit of random sets using topological data analysis. We construct the filtration from level sets of the signed distance function and consider various summary functions of the persistence diagram derived from the obtained persistence homology. The outliers are detected using functional depths for the summary functions. Global envelope tests using the summary statistics as test statistics were used to construct the goodness-of-fit test. The procedures were justified by a simulation study using germ-grain random set models.
format Preprint
id arxiv_https___arxiv_org_abs_2404_04702
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Topological data analysis for random sets and its application in detecting outliers and goodness of fit testing
Đogaš, Vesna Gotovac
Mandarić, Marcela
Methodology
60D05, 62R40, 55N31
G.3
In this paper we present the methodology for detecting outliers and testing the goodness-of-fit of random sets using topological data analysis. We construct the filtration from level sets of the signed distance function and consider various summary functions of the persistence diagram derived from the obtained persistence homology. The outliers are detected using functional depths for the summary functions. Global envelope tests using the summary statistics as test statistics were used to construct the goodness-of-fit test. The procedures were justified by a simulation study using germ-grain random set models.
title Topological data analysis for random sets and its application in detecting outliers and goodness of fit testing
topic Methodology
60D05, 62R40, 55N31
G.3
url https://arxiv.org/abs/2404.04702