Testing the adequacy of a linear modelVIAcritical smoothing

DOI10.1080/00949650108812070zbMath0967.62028OpenAlexW2070092061MaRDI QIDQ2720220

Li-Shan Huang

Publication date: 2 September 2001

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650108812070

zbMATH Keywords

kernel density estimationlocal linear regressionwild bootstrap

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Linear regression; mixed models (62J05) Nonparametric statistical resampling methods (62G09)

Related Items (1)

Bandwidth-based nonparametric inference

Cites Work

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• Semiparametric comparison of regression curves
• Comparing nonparametric versus parametric regression fits
• Testing the hypothesis of a general linear model using nonparametric regression estimation
• Nonparametric smoothing and lack-of-fit tests
• Smoothing methods in statistics
• Bootstrap and wild bootstrap for high dimensional linear models
• Asymptotically optimal difference-based estimation of variance in nonparametric regression
• On the use of nonparametric regression for model checking
• A cubic spline extension of the Durbin-Watson test
• Diagnostics for Assessing Regression Models
• Kernel Regression When the Boundary Region is Large, With an Application to Testing the Adequacy of Polynomial Models
• Non-Parametric Analysis of Covariance

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