Influence of design on the rate of convergence to normality in L1 regression

DOI10.1017/S0305004100078166zbMath0735.62047OpenAlexW2162736562MaRDI QIDQ3982608

A. H. Welsh

Publication date: 26 June 1992

Published in: Mathematical Proceedings of the Cambridge Philosophical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s0305004100078166

zbMATH Keywords

momentsconvergence rateEdgeworth expansionBerry-Esseen rateL1-regressioninfluence of design variablesmoment condition on the error distributionnon-uniform Berry- Esseen theorem

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05)

Related Items (1)

Robust empirical likelihood for linear models under median constraints

Cites Work

• Unnamed Item
• Asymptotic expansions for sample quantiles
• On the accuracy of the normal approximation for quantiles
• Asymptotic Theory of Least Absolute Error Regression
• Probability Inequalities for Sums of Bounded Random Variables

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