Design-adaptive nonparametric estimation of conditional quantile derivatives

DOI10.1080/10485252.2012.688826zbMath1254.62051OpenAlexW1999594140MaRDI QIDQ3145385

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Publication date: 20 December 2012

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

Full work available at URL: https://doi.org/10.1080/10485252.2012.688826

zbMATH Keywords

kernel estimatesnonparametric regressionlocal polynomials

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) General nonlinear regression (62J02) Monte Carlo methods (65C05)

Related Items

Local linear double and asymmetric kernel estimation of conditional quantiles

Cites Work

• Unnamed Item
• Quantile regression methods for recursive structural equation models
• Characterization of the asymptotic distribution of semiparametric M-estimators
• Nonparametric estimates of regression quantiles and their local Bahadur representation
• Consistent nonparametric regression. Discussion
• On average derivative quantile regression
• Limiting distributions for \(L_1\) regression estimators under general conditions
• Design-adaptive Nonparametric Regression
• Regression Quantiles
• Quantile smoothing splines
• A Semiparametric Maximum Likelihood Estimator
• On an Analog of Regression Analysis