Asymptotic normality of convergent estimates of conditional quantiles

Alain Berlinet; Ali Gannoun; Eric Atzner-løber

doi:10.1080/02331880108802728

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Asymptotic normality of convergent estimates of conditional quantiles

Article de revue

Avec comité de lecture

Asymptotic normality of convergent estimates of conditional quantiles

Alain Berlinet, Ali Gannoun et Eric Atzner-løber

Statistics (Berlin, DDR), Vol.35(2), pp.139-169

01/01/2001

DOI: https://doi.org/10.1080/02331880108802728

Résumé

Asymptotic normality

Conditional quantiles

Forecasting

Time series

α-mixing stationary processes

We state sufficient conditions for asymptotic normality of convergent estimates of conditional quantiles, irrespective of data dependence and consider the particular case of α-mixing stationary processes under optimal condition of convergence. We apply this result to confidence intervals building for time series predictors based on nonparametric estimates of the conditional median.

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Détails

Titre: Asymptotic normality of convergent estimates of conditional quantiles
Créateurs - sans rôle: Alain Berlinet - University of Montpellier II
Ali Gannoun - University of Montpellier II
Eric Atzner-løber - University of Montpellier II
Détails de publication: Statistics (Berlin, DDR), Vol.35(2), pp.139-169
Éditeur: Gordon & Breach Science Publishers
Nombre de pages: 31
Identifiants: 99162862009311
Unité académique: Institut Montpelliérain Alexander Grothendieck - IMAG
Langue: English
Type de ressource: Journal article