Stochastic convergence of persistence landscapes and silhouettes

<p>Persistent homology is a widely used tool in Topological Data Analysis that encodes multi-scale topological information as a multiset of points in the plane called a persistence diagram. It is difficult to apply statistical theory directly to a random sample of diagrams. Instead, we summari...

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Main Authors: Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Larry Wasserman
Format: Article
Language:English
Published: Carleton University 2015-03-01
Series:Journal of Computational Geometry
Online Access:http://jocg.org/index.php/jocg/article/view/203
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spelling doaj-bb41563c58104972aa5edb5a64b70f272020-11-24T23:05:08ZengCarleton UniversityJournal of Computational Geometry1920-180X2015-03-016210.20382/jocg.v6i2a866Stochastic convergence of persistence landscapes and silhouettesFrédéric ChazalBrittany Terese FasyFabrizio LecciAlessandro RinaldoLarry Wasserman<p>Persistent homology is a widely used tool in Topological Data Analysis that encodes multi-scale topological information as a multiset of points in the plane called a persistence diagram. It is difficult to apply statistical theory directly to a random sample of diagrams. Instead, we summarize persistent homology with a persistence landscape, introduced by Bubenik, which converts a diagram into a well-behaved real-valued function. We investigate the statistical properties of landscapes, such as weak convergence of the average landscapes and convergence of the bootstrap. In addition, we introduce an alternate functional summary of persistent homology, which we call the silhouette, and derive an analogous statistical theory.</p>http://jocg.org/index.php/jocg/article/view/203
collection DOAJ
language English
format Article
sources DOAJ
author Frédéric Chazal
Brittany Terese Fasy
Fabrizio Lecci
Alessandro Rinaldo
Larry Wasserman
spellingShingle Frédéric Chazal
Brittany Terese Fasy
Fabrizio Lecci
Alessandro Rinaldo
Larry Wasserman
Stochastic convergence of persistence landscapes and silhouettes
Journal of Computational Geometry
author_facet Frédéric Chazal
Brittany Terese Fasy
Fabrizio Lecci
Alessandro Rinaldo
Larry Wasserman
author_sort Frédéric Chazal
title Stochastic convergence of persistence landscapes and silhouettes
title_short Stochastic convergence of persistence landscapes and silhouettes
title_full Stochastic convergence of persistence landscapes and silhouettes
title_fullStr Stochastic convergence of persistence landscapes and silhouettes
title_full_unstemmed Stochastic convergence of persistence landscapes and silhouettes
title_sort stochastic convergence of persistence landscapes and silhouettes
publisher Carleton University
series Journal of Computational Geometry
issn 1920-180X
publishDate 2015-03-01
description <p>Persistent homology is a widely used tool in Topological Data Analysis that encodes multi-scale topological information as a multiset of points in the plane called a persistence diagram. It is difficult to apply statistical theory directly to a random sample of diagrams. Instead, we summarize persistent homology with a persistence landscape, introduced by Bubenik, which converts a diagram into a well-behaved real-valued function. We investigate the statistical properties of landscapes, such as weak convergence of the average landscapes and convergence of the bootstrap. In addition, we introduce an alternate functional summary of persistent homology, which we call the silhouette, and derive an analogous statistical theory.</p>
url http://jocg.org/index.php/jocg/article/view/203
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