Smooth quantile estimators under strong mixing: necessary and sufficient conditions on bandwidth for weak convergence

DOI10.1016/J.JSPI.2003.11.006zbMath1056.62046OpenAlexW2068077903MaRDI QIDQ707051

Minerva Cordero, Shan Sun

Publication date: 9 February 2005

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2003.11.006

zbMATH Keywords

stationary strong mixing

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05)

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Bootstrap variance estimation for Nadaraya quantile estimator ⋮ A semiparametric single index model with heterogeneous impacts on an unobserved variable

Cites Work

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• Weak convergence of smoothed and nonsmoothed bootstrap quantile estimates
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• Perturbed empirical distribution functions and quantiles under dependence
• Necessary and sufficient conditions for the asymptotic normality of perturbed sample quantiles
• A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
• A Smooth Nonparametric Estimator of a Quantile Function
• Nonparametric Statistical Data Modeling
• Some New Estimates for Distribution Functions
• The Asymptotic Inadmissibility of the Sample Distribution Function
• Some Limit Theorems for Stationary Processes

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