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Local bilinear multiple-output quantile/depth regression

Result description

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 providedboth on simulated and real data.

Keywords

conditional depthgrowth charthalfspace depthlocal bilinear regressionmultivariate quantilequantile regressionregression depth

The result's identifiers

Alternative languages

  • Result language

    angličtina

  • Original language name

    Local bilinear multiple-output quantile/depth regression

  • Original language description

    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 providedboth on simulated and real data.

  • Czech name

  • Czech description

Classification

  • Type

    Jx - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Bernoulli

  • ISSN

    1350-7265

  • e-ISSN

  • Volume of the periodical

    21

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    32

  • Pages from-to

    1435-1466

  • UT code for WoS article

    000356993100007

  • EID of the result in the Scopus database

    2-s2.0-84938592517

Basic information

Result type

Jx - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

Jx

CEP

BA - General mathematics

Year of implementation

2015