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Halfspace Depth

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10507222" target="_blank" >RIV/00216208:11320/25:10507222 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=GhdNtWbDm3" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=GhdNtWbDm3</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/wics.70038" target="_blank" >10.1002/wics.70038</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Halfspace Depth

  • Original language description

    The halfspace depth (HD, also called Tukey depth) is a nonparametric tool of multivariate statistics that has found many applications in exploratory analysis, estimation, and statistical testing. For a dataset, it can be defined as the minimum portion of data points in the d$$ d $$-space that can be cut off by a hyperplane passing through a given point; in a probabilistic setting, it is defined as the smallest probability of a closed halfspace containing a given point. The HD can be seen as a generalization of quantiles to multivariate data based on a projection pursuit principle. It naturally induces a robust multivariate median, and the contours of the HD function give information about the geometry of the underlying dataset/probability distribution. We provide a high-level overview of the most important theoretical properties and applications of the HD for multivariate data. We also outline several extensions of the HD to additional settings, such as halfspace-like depths for directional, object, or functional data. This article is categorized under: Statistical and Graphical Methods of Data Analysis &gt; Multivariate Analysis Statistical and Graphical Methods of Data Analysis &gt; Nonparametric Methods Statistical and Graphical Methods of Data Analysis &gt; Robust Methods

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • 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

  • Name of the periodical

    Wiley Interdisciplinary Reviews. Computational statistics

  • ISSN

    1939-5108

  • e-ISSN

    1939-0068

  • Volume of the periodical

    17

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    18

  • Pages from-to

    e70038

  • UT code for WoS article

    001540706400001

  • EID of the result in the Scopus database

    2-s2.0-105011691112