On nonparametric regression estimators based on regression quantiles

DOI10.1080/03610928708829374zbMath0655.62037OpenAlexW2073069716MaRDI QIDQ3802410

Noël Veraverbeke, Paul Janssen

Publication date: 1987

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928708829374

zbMATH Keywords

asymptotic normalityBahadur representationremainder termstrong consistency ratelinear combinations of regression quantiles

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Inequalities; stochastic orderings (60E15) Nonparametric estimation (62G05)

Related Items

Bounded length confidence intervals in nonparametric regression, Global nonparametric estimation of conditional quantile functions and their derivatives, Nonparametric regression M-quantiles, Bootstrapping regression quantiles

Cites Work

• The central limit theorem for dependent random variables
• Approximation Theorems of Mathematical Statistics
• A New Proof of the Bahadur Representation of Quantiles and an Application