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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
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
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
Linking options:
https://www.mathnet.ru/eng/tvp4https://doi.org/10.4213/tvp4 https://www.mathnet.ru/eng/tvp/v52/i1/p60
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Abstract page: | 496 | Full-text PDF : | 158 | References: | 42 | First page: | 12 |
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