Testing homoscedasticity in nonparametric regression

DOI10.1080/10485250306038zbMath1019.62036OpenAlexW2050750671MaRDI QIDQ4709835

Hannelore Liero

Publication date: 29 September 2003

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

Full work available at URL: https://doi.org/10.1080/10485250306038

zbMATH Keywords

kernel estimatorsheteroscedasticityrandom designvariance estimatorsconditional \(U\)-statisticsISE

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10)

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Cites Work

• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• Strong uniform consistency of nonparametric regression function estimates
• The power and optimal kernel of the Bickel-Rosenblatt test for goodness of fit
• Conditional \(U\)-statistics
• Asymptotic normality of a weighted integrated squared error of kernel regression estimates with data-dependent bandwidth
• A quadratic measure of deviation of two-dimensional density estimates and a test of independence
• A global measure of a spline density estimate
• On some global measures of the deviations of density function estimates
• Asymptotically optimal difference-based estimation of variance in nonparametric regression
• Nonparametric estimation of residual variance revisited
• Residual variance and residual pattern in nonlinear regression
• Weak and strong uniform consistency of kernel regression estimates

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