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Parametric Elliptical Regression Quantiles

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F20%3A00493763" target="_blank" >RIV/67985556:_____/20:00493763 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11320/20:10419381

  • Result on the web

    <a href="https://www.ine.pt/revstat/pdf/ONPARAMETRICELLIPTICALREGRESSIONQUANTILES.pdf" target="_blank" >https://www.ine.pt/revstat/pdf/ONPARAMETRICELLIPTICALREGRESSIONQUANTILES.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Parametric Elliptical Regression Quantiles

  • Original language description

    The article extends linear and nonlinear quantile regression to the case of vector responses by generalizing multivariate elliptical quantiles to a regression context. In particular, it introduces parametric elliptical quantile regression in a general nonlinear multivariate heteroscedastic framework and discusses, investigates, and illustrates the new method in some detail, including basic properties, various parametrizations, possible heteroscedastic patterns, related computational issues, model validation, and a real biometric data example. The method seems suitable for multi-response regression models with symmetric errors, especially if the dimension of responses is less than ten and if the right parametrization of the model follows from the context.

  • 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

    10101 - Pure mathematics

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Revstat Statistical Journal

  • ISSN

    1645-6726

  • e-ISSN

  • Volume of the periodical

    18

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    PT - PORTUGAL

  • Number of pages

    27

  • Pages from-to

    257-280

  • UT code for WoS article

    000557809200002

  • EID of the result in the Scopus database

    2-s2.0-85090693948