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This article is cited in 7 scientific papers (total in 7 papers)
The Berry–Esseen bound for $\rho$-mixing random variables and its applications in nonparametric regression model
X. J. Wang, S. H. Hu School of Mathematical Sciences, Anhui University, Hefei 230601, P. R. China
Abstract:
In this paper, the Berry–Esseen bound for $\rho$-mixing random variables with the rate of normal approximation
$O(n^{-1/6}\log n)$ is established under some suitable conditions. By using the Berry–Esseen bound, we further investigate the
Berry–Esseen bound of sample quantiles for $\rho$-mixing random
variables. The rate of normal approximation is shown to be $O(n^{-1/6}\log n)$ under some suitable conditions. In addition,
the asymptotic normality of the linear weighted estimator for the nonparametric regression model based on $\rho$-mixing errors is
studied by using the Berry–Esseen bound that we established. Some new results are obtained in the paper under much weaker dependent structures.
Keywords:
Berry–Esseen bound, normal approximation, nonparametric regression model, sample quantiles, $\rho$-mixing sequence.
Received: 12.06.2016 Revised: 14.12.2017 Accepted: 05.04.2018
Citation:
X. J. Wang, S. H. Hu, “The Berry–Esseen bound for $\rho$-mixing random variables and its applications in nonparametric regression model”, Teor. Veroyatnost. i Primenen., 63:3 (2018), 584–608; Theory Probab. Appl., 63:3 (2019), 479–499
Linking options:
https://www.mathnet.ru/eng/tvp5197https://doi.org/10.4213/tvp5197 https://www.mathnet.ru/eng/tvp/v63/i3/p584
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