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Teoriya Veroyatnostei i ee Primeneniya, 2007, Volume 52, Issue 1, Pages 60–68
DOI: https://doi.org/10.4213/tvp4
(Mi tvp4)
 

This article is cited in 4 scientific papers (total in 4 papers)

On normal approximation for strongly mixing random fields

J. Sunklodas

Institute of Mathematics and Informatics
Full-text PDF (688 kB) Citations (4)
References:
Abstract: In this paper, we estimate the difference $|\mathbf Eh(Z_V)-\mathbf Eh(N)|$, where $Z_V$ is a sum over any finite subset $V$ of the standard lattice $\mathbf Z^d$ of normalized random variables of the strongly mixing random field $\{X_a,\ a\in\mathbf Z^d\}$ (without assuming stationarity) and $N$ is a standard normal random variable for the function $h\colon\mathbf R\to\mathbf R$, which is finite and satisfies the Lipschitz condition. In a particular case, the obtained upper bounds of $|\mathbf Eh(Z_V)-\mathbf Eh(N)|$ in Theorems 3 and 4 are of order $O(|V|^{-1/2})$.
Keywords: normal approximations, bounded Lipschitz metrics, random fields, strong mixing condition, method of Stein.
Received: 25.05.2004
English version:
Theory of Probability and its Applications, 2008, Volume 52, Issue 1, Pages 125–132
DOI: https://doi.org/10.1137/S0040585X97982815
Bibliographic databases:
Language: Russian
Citation: J. Sunklodas, “On normal approximation for strongly mixing random fields”, Teor. Veroyatnost. i Primenen., 52:1 (2007), 60–68; Theory Probab. Appl., 52:1 (2008), 125–132
Citation in format AMSBIB
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  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Теория вероятностей и ее применения Theory of Probability and its Applications
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