Asymptotics of kernel estimators based on local maximum likelihood

DOI10.1080/10485259408832602zbMath1380.62162OpenAlexW2040092418MaRDI QIDQ3432397

Peng-Liang Zhao

Publication date: 16 April 2007

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

Full work available at URL: https://doi.org/10.1080/10485259408832602

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

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Cites Work

• Uniform consistency of a class of regression function estimators
• Strong uniform consistency rates for estimators of conditional functionals
• Asymptotic properties of kernel estimators based on local medians
• Weak and strong uniform consistency of the kernel estimate of a density and its derivatives
• Optimal global rates of convergence for nonparametric regression
• Local Likelihood Estimation
• Finding extrema and zeros in nonparametric regression when the data contains outliers
• Joint Asymptotic Distribution of the Estimated Regression Function at a Finite Number of Distinct Points
• The Kernel Estimate of a Regression Function in Likelihood-Based Models

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