Propriétés asymptotiques d'estimateurs convergents des quantiles conditionnels

Alain Berlinet; Ali Gannoun; Eric Matzner-Løber

doi:10.1016/S0764-4442(98)85016-7

Propriétés asymptotiques d'estimateurs convergents des quantiles conditionnels

Translated title of the contribution: Asymptotic properties of convergent estimators of conditional quantiles

Alain Berlinet
, Ali Gannoun
, Eric Matzner-Løber

University of Montpellier (UMR MiVEGEC)

Research output: Contribution to journal › Article › peer-review

Abstract

We state sufficient conditions for asymptotic normality of convergent estimates of the conditional quantiles, irrespective of data dependence, and give an application to α-mixing stationary processes, under optimal conditions. As an application, we use asymptotic normality to construct confidence bands for predictors based on nonparametric estimates of the conditional median.

Translated title of the contribution	Asymptotic properties of convergent estimators of conditional quantiles
Original language	French
Pages (from-to)	611-614
Number of pages	4
Journal	Comptes Rendus de l'Academie des Sciences - Series I: Mathematics
Volume	326
Issue number	5
DOIs	https://doi.org/10.1016/S0764-4442(98)85016-7
Publication status	Published - 1 Jan 1998
Externally published	Yes

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10.1016/S0764-4442(98)85016-7

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title = "Propri{\'e}t{\'e}s asymptotiques d'estimateurs convergents des quantiles conditionnels",

abstract = "We state sufficient conditions for asymptotic normality of convergent estimates of the conditional quantiles, irrespective of data dependence, and give an application to α-mixing stationary processes, under optimal conditions. As an application, we use asymptotic normality to construct confidence bands for predictors based on nonparametric estimates of the conditional median.",

author = "Alain Berlinet and Ali Gannoun and Eric Matzner-L{\o}ber",

year = "1998",

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AU - Berlinet, Alain

AU - Gannoun, Ali

AU - Matzner-Løber, Eric

PY - 1998/1/1

Y1 - 1998/1/1

N2 - We state sufficient conditions for asymptotic normality of convergent estimates of the conditional quantiles, irrespective of data dependence, and give an application to α-mixing stationary processes, under optimal conditions. As an application, we use asymptotic normality to construct confidence bands for predictors based on nonparametric estimates of the conditional median.

AB - We state sufficient conditions for asymptotic normality of convergent estimates of the conditional quantiles, irrespective of data dependence, and give an application to α-mixing stationary processes, under optimal conditions. As an application, we use asymptotic normality to construct confidence bands for predictors based on nonparametric estimates of the conditional median.

UR - https://www.scopus.com/pages/publications/0038900067

U2 - 10.1016/S0764-4442(98)85016-7

DO - 10.1016/S0764-4442(98)85016-7

M3 - Article

AN - SCOPUS:0038900067

SN - 0764-4442

VL - 326

SP - 611

EP - 614

JO - Comptes Rendus de l'Academie des Sciences - Series I: Mathematics

JF - Comptes Rendus de l'Academie des Sciences - Series I: Mathematics

IS - 5

ER -

Propriétés asymptotiques d'estimateurs convergents des quantiles conditionnels

Abstract

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