Počet záznamů: 1  

Local bilinear multiple-output quantile/depth regression

  1. 1. 0446857 - UTIA-B 2016 RIV NL eng J - Článek v odborném periodiku
    Hallin, M. - Lu, Z. - Paindaveine, D. - Šiman, Miroslav
    Local bilinear multiple-output quantile/depth regression.
    Bernoulli. Roč. 21, č. 3 (2015), s. 1435-1466. ISSN 1350-7265
    Grant CEP: GA MŠk(CZ) 1M06047
    Institucionální podpora: RVO:67985556
    Klíčová slova: conditional depth * growth chart * halfspace depth * local bilinear regression * multivariate quantile * quantile regression * regression depth
    Kód oboru RIV: BA - Obecná matematika
    Impakt faktor: 1.372, rok: 2015

    A new quantile regression concept, based on a directional version of Koenker and Bassett's traditional single-output one, has been introduced in [Ann. Statist. (2010) 38 635-669] for multiple-output location/linear regression problems. The polyhedral contours provided by the empirical counterpart of that concept, however, cannot adapt to unknown nonlinear and/or heteroskedastic dependencies. This paper therefore introduces local constant and local linear (actually, bilinear) versions of those contours, which both allow to asymptotically recover the conditional halfspace depth contours that completely characterize the response's conditional distributions. Bahadur representation and asymptotic normality results are established. Illustrations are provided both on simulated and real data.
    Trvalý link: http://hdl.handle.net/11104/0248946