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.

Christophe Ange Napoléon Biscio; Jesper Møller

doi:10.1080/10618600.2019.1573686

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.

Christophe Ange Napoléon Biscio^*, Jesper Møller

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

32 Citations (Scopus)

Original language	English
Journal	Journal of Computational and Graphical Statistics
Volume	28
Issue number	3
Pages (from-to)	671-681
Number of pages	11
ISSN	1061-8600
DOIs	https://doi.org/10.1080/10618600.2019.1573686
Publication status	Published - 2019

Keywords

Clustering
Confidence region
Functional boxplot
Global rank envelope
Persistent homology
Two-sample test

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10.1080/10618600.2019.1573686

https://arxiv.org/abs/1611.00630

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Cite this

@article{b1d3392d2a2048f6abb1920fae4de067,

title = "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.",

keywords = "Clustering, Confidence region, Functional boxplot, Global rank envelope, Persistent homology, Two-sample test",

author = "Biscio, {Christophe Ange Napol{\'e}on} and Jesper M{\o}ller",

year = "2019",

doi = "10.1080/10618600.2019.1573686",

language = "English",

volume = "28",

pages = "671--681",

journal = "Journal of Computational and Graphical Statistics",

issn = "1061-8600",

publisher = "Taylor & Francis",

number = "3",

}

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. / Biscio, Christophe Ange Napoléon ; Møller, Jesper.
In: Journal of Computational and Graphical Statistics, Vol. 28, No. 3, 2019, p. 671-681.

Research output: Contribution to journal › Journal article › Research › peer-review

TY - JOUR

T1 - 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.

AU - Biscio, Christophe Ange Napoléon

AU - Møller, Jesper

PY - 2019

Y1 - 2019

KW - Clustering

KW - Confidence region

KW - Functional boxplot

KW - Global rank envelope

KW - Persistent homology

KW - Two-sample test

UR - http://www.scopus.com/inward/record.url?scp=85065210781&partnerID=8YFLogxK

U2 - 10.1080/10618600.2019.1573686

DO - 10.1080/10618600.2019.1573686

M3 - Journal article

SN - 1061-8600

VL - 28

SP - 671

EP - 681

JO - Journal of Computational and Graphical Statistics

JF - Journal of Computational and Graphical Statistics

IS - 3

ER -

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.

Keywords

Access to Document

AUB Link

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