Testing for a constant coefficient of variation in nonparametric regression by empirical processes

DOI10.1007/s10463-011-0346-5zbMath1254.62048OpenAlexW2039006703MaRDI QIDQ1926008

Jens Wagener, Mareen Marchlewski, Dette, Holger

Publication date: 27 December 2012

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-011-0346-5

zbMATH Keywords

empirical processes

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05)

Related Items (4)

Asymptotic distribution-free tests for semiparametric regressions with dependent data ⋮ Exploring the constant coefficient of a single-index variation ⋮ Comments on: ``An updated review of goodness-of-fit tests for regression models ⋮ Convergence rates for kernel regression in infinite-dimensional spaces

Cites Work

• On the estimation of a monotone conditional variance in nonparametric regression
• Nonparametric model checks for regression
• Testing for a constant coefficient of variation in nonparametric regression
• Goodness-of-Fit Tests for Multiplicative Models with Dependent Data
• Robust Tests for Heteroscedasticity Based on Regression Quantiles
• Testing Heteroscedasticity In Nonparametric Regression
• Efficient estimation of conditional variance functions in stochastic regression
• Local Polynomial Variance-Function Estimation
• A central limit theorem with applications to random hypergraphs
• Likelihood-Based Local Linear Estimation of the Conditional Variance Function
• Designs for Regression Problems with Correlated Errors
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