Conditional \(L_ p\)-quantiles and their application to the testing of symmetry in non-parametric regression

DOI10.1016/0167-7152(95)00163-8zbMath0865.62021OpenAlexW2094407065MaRDI QIDQ1126090

Zehua Chen

Publication date: 8 December 1996

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(95)00163-8

zbMATH Keywords

asymptotic normalitykernel estimatesregression quantilesnonparametric regressiontesting of symmetry

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20)

Related Items (17)

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Cites Work

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• Asymmetric Least Squares Estimation and Testing
• Nonparametric estimates of regression quantiles and their local Bahadur representation
• Kernel and nearest-neighbor estimation of a conditional quantile
• Convergence of sample paths of normalized sums of induced order statistics
• Nonparametric regression M-quantiles
• Robust Tests for Heteroscedasticity Based on Regression Quantiles
• Regression Quantiles
• Quantile smoothing splines

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