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Multivariate and functional covariates and conditional copulas

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10125963" target="_blank" >RIV/00216208:11320/12:10125963 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1214/12-EJS712" target="_blank" >http://dx.doi.org/10.1214/12-EJS712</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1214/12-EJS712" target="_blank" >10.1214/12-EJS712</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Multivariate and functional covariates and conditional copulas

  • Original language description

    In this paper the interest is to estimate the dependence between two variables conditionally upon a covariate, through copula modelling. In recent literature nonparametric estimators for conditional copula functions in case of a univariate covariate havebeen proposed. The aim of this paper is to nonparametrically estimate a conditional copula when the covariate takes on values in more complex spaces. We consider multivariate covariates and functional covariates. We establish weak convergence, and biasand variance properties of the proposed nonparametric estimators. We also briefly discuss nonparametric estimation of conditional association measures such as a conditional Kendalls tau. The case of functional covariates is of particular interest and challenge, both from theoretical as well as practical point of view. For this setting we provide an illustration with a real data example in which the covariates are spectral curves. A simulation study investigating the finite-sample perform

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GPP201%2F11%2FP290" target="_blank" >GPP201/11/P290: Methods of statistical inference based on a distance matrix</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2012

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Electronic Journal of Statistics

  • ISSN

    1935-7524

  • e-ISSN

  • Volume of the periodical

    6

  • Issue of the periodical within the volume

    Neuveden

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    34

  • Pages from-to

    1273-1306

  • UT code for WoS article

    000306920500001

  • EID of the result in the Scopus database