Conditional \(L_ p\)-quantiles and their application to the testing of symmetry in non-parametric regression
type: Item
instance of: scholarly article
title: Conditional \(L_ p\)-quantiles and their application to the testing of symmetry in non-parametric regression
zbMATH Open document ID: 0865.62021
DOI: 10.1016/0167-7152(95)00163-8
author: Zehua Chen
published in: Statistics \& Probability Letters
publication date: 1996-12-08T00:00:00Z
Mathematics Subject Classification ID: 62G07
Mathematics Subject Classification ID: 62G10
Mathematics Subject Classification ID: 62G20
zbMATH DE Number: 954926
zbMATH Keywords: regression quantiles
zbMATH Keywords: nonparametric regression
zbMATH Keywords: asymptotic normality
zbMATH Keywords: kernel estimates
zbMATH Keywords: testing of symmetry
MaRDI profile type: Publication
full work available at URL: 0167-7152(95)00163-8
OpenAlex ID: W2094407065
cites work: Nonparametric regression M-quantiles
cites work: Convergence of sample paths of normalized sums of induced order statistics
cites work: Kernel and nearest-neighbor estimation of a conditional quantile
cites work: Nonparametric estimates of regression quantiles and their local Bahadur representation
cites work: Q5545069
cites work: Q3332084
cites work: Regression Quantiles
cites work: Robust Tests for Heteroscedasticity Based on Regression Quantiles
cites work: Quantile smoothing splines
cites work: Asymmetric Least Squares Estimation and Testing
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description: scientific article; zbMATH DE number 954926