Statistical inference on heteroscedastic models based on regression quantiles

DOI10.1080/10485259808832745zbMath0911.62059OpenAlexW2038812658MaRDI QIDQ4222481

Kenneth Q. Zhou, Stephen L. Portnoy

Publication date: 14 March 1999

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485259808832745

zbMATH Keywords

Bahadur representationBrownian bridgedirect methodconditional quantilesleast absolute deviationsempirical levlesLAD residuals

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Nonparametric tolerance and confidence regions (62G15)

Related Items

Conformal Prediction: A Gentle Introduction, Rank score and permutation testing alternatives for regression quantile estimates, Constrained quantile regression and heteroskedasticity, Nonparametric inference on smoothed quantile regression process, Instability of least squares, least absolute deviation and least median of squares linear regression. (With a comment and a rejoinder)., On monotonicity of regression quantile functions, Robust weighted LAD regression, Asymptotics for L₁‐estimators of regression parameters under heteroscedasticityY, Quantile regression for dynamic panel data with fixed effects

Uses Software

• alr3

Cites Work

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