The accumulated persistence function, a new useful functional summary statistic for topological data analysis, with a view to brain artery trees and spatial point process applications.

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Resumé

We start with a simple introduction to topological data analysis where the most popular tool is called a persistent diagram. Briefly, a persistent diagram is a multiset of points in the plane describing the persistence of topological features of a compact set when a scale parameter varies. Since statistical methods are difficult to apply directly on persistence diagrams, various alternative functional summary statistics have been suggested, but either they do not contain the full information of the persistence diagram or they are two-dimensional functions. We suggest a new functional summary statistic that is one-dimensional and hence easier to handle, and which under mild conditions contains the full information of the persistence diagram. Its usefulness is illustrated in statistical settings concerned with point cloudsand brain artery trees. The appendix includes additional methods and examples, together with technical details. The R-code used for all examples is available at http://people.math.aau.dk/~christophe/Rcode.zip
OriginalsprogEngelsk
TidsskriftJournal of Computational and Graphical Statistics
Antal sider45
ISSN1061-8600
DOI
StatusE-pub ahead of print - 2019

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Spatial Point Process
Arteries
Persistence
Statistic
Data analysis
Diagram
Multiset
Point Cloud
Scale Parameter
Compact Set
Statistical method
Brain
Point process
Statistics
Diagrams
Vary
Alternatives

Citer dette

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abstract = "We start with a simple introduction to topological data analysis where the most popular tool is called a persistence diagram. Briefly, a persistence diagram is a multiset of points in the plane describing the persistence of topological features of a compact set when a scale parameter varies. Since statistical methods are difficult to apply directly on persistence diagrams, various alternative functional summary statistics have been suggested, but either they do not contain the full information of the persistence diagram or they are two-dimensional functions. We suggest a new functional summary statistic that is one-dimensional and hence easier to handle, and which under mild conditions contains the full information of the persistence diagram. Its usefulness is illustrated in statistical settings concerned with point clouds and brain artery trees. The supplementary materials include additional methods and examples, technical details, and the R code used for all examples.",
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