Berry–Esseen type bound of conditional mode estimation under truncation and strong mixing assumptions

DOI10.1080/03610926.2014.936561zbMath1346.62070OpenAlexW2471218300MaRDI QIDQ2817136

Tianxuan Miao, Han-Ying Liang, De Li Li

Publication date: 29 August 2016

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2014.936561

Mathematics Subject Classification ID

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

Related Items (2)

The Berry–Esseen-type bound for the G-M estimator in a nonparametric regression model with α-mixing errors ⋮ The Berry-Esseen type bounds of the weighted estimator in a nonparametric model with linear process errors

Cites Work

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• Asymptotic properties of the kernel estimator of the conditional mode for the left truncated model
• Berry-Esseen type bounds of estimators in a semiparametric model with linear process errors
• Strong convergence in nonparametric regression with truncated dependent data
• Asymptotic normality for estimator of conditional mode under left-truncated and dependent observations
• Strong convergence of sums of \(\alpha \)-mixing random variables with applications to density estimation
• Nonparametric quantile estimation with correlated failure time data
• Large deviations and law of the iterated logarithm for partial sums normalized by the largest absolute observation
• Estimating a distribution function with truncated data

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