Illumination Depth
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10435405" target="_blank" >RIV/00216208:11320/21:10435405 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DT.l~fHPFH" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DT.l~fHPFH</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/10618600.2020.1776717" target="_blank" >10.1080/10618600.2020.1776717</a>
Alternative languages
Result language
angličtina
Original language name
Illumination Depth
Original language description
The concept of illumination bodies studied in convex geometry is used to amend the halfspace depth for multivariate data. The proposed notion of illumination enables finer resolution of the sample points, naturally breaks ties in the associated depth-based ordering, and introduces a depth-like function for points outside the convex hull of the support of the probability measure. The illumination is, in a certain sense, dual to the halfspace depth mapping, and shares the majority of its beneficial properties. It is affine invariant, robust, uniformly consistent, and aligns well with common probability distributions. Supplementary materials for this article are available online.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GJ19-16097Y" target="_blank" >GJ19-16097Y: Geometric aspects of mathematical statistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Computational and Graphical Statistics
ISSN
1061-8600
e-ISSN
—
Volume of the periodical
30
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
78-90
UT code for WoS article
000546744800001
EID of the result in the Scopus database
2-s2.0-85087734912