Nonparametric, multidimensional estimation of regression derivatives.

DOI10.1016/j.crma.2004.09.024zbMath1075.62028OpenAlexW1997160054MaRDI QIDQ1763494

David Blondin

Publication date: 22 February 2005

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.crma.2004.09.024

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

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Cites Work

• Functional laws of the iterated logarithm for the increments of empirical and quantile processes
• Contributions to the theory of nonparametric regression, with application to system identification
• General asymptotic confidence bands based on kernel-type function estimators
• Weak convergence and empirical processes. With applications to statistics
• The Law of the Iterated Logarithm for Empirical Distribution
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