The Spherical Depth for Functional Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10506429" target="_blank" >RIV/00216208:11320/25:10506429 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-92383-8_48" target="_blank" >https://doi.org/10.1007/978-3-031-92383-8_48</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-92383-8_48" target="_blank" >10.1007/978-3-031-92383-8_48</a>
Alternative languages
Result language
angličtina
Original language name
The Spherical Depth for Functional Data
Original language description
In the nonparametric analysis of multivariate data, the spherical depth of a point x is an element of R-d with respect to a distribution P on R-d is the probability that a ball, determined by two antipodal points on its boundary that are sampled independently from P, covers x. The greatest advantage of the spherical depth is its fast computation, which is, unlike for many other depth functions, not exponential in the dimension d. That makes the spherical depth amenable for the analysis of high-dimensional, and functional data. We explore the theory and practice of spherical depth when applied to data of high dimensionality. In particular, we point to several difficulties with known results in the literature and revise multiple classical propositions on the behavior of spherical depth.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
NEW TRENDS IN FUNCTIONAL STATISTICS AND RELATED FIELDS
ISBN
978-3-031-92382-1
ISSN
1431-1968
e-ISSN
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Number of pages
8
Pages from-to
401-408
Publisher name
SPRINGER INTERNATIONAL PUBLISHING AG
Place of publication
CHAM
Event location
Novara
Event date
Jun 25, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001545850800048