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Theoretical Foundations of Applied Discrete Mathematics
The rate of normal approximation for the distribution of the number of multiple repetitions of characters in a stationary random sequence
V. G. Mikhailova, N. M. Mezhennayab a Steklov Mathematical Institute of Russian Academy of Sciences, Moscow
b Bauman Moscow State Technical University
Abstract:
We study the asymptotic normality of the number of $r$-fold characters repetitions in a segment of length $n$ of a strictly stationary random sequence with values in a finite set that satisfies the uniformly strong mixing condition. It is shown that if there exists a number $\alpha> 0$ such that the uniformly strong mixing coefficient $\varphi(t)$ decreases as $t^{-6-\alpha}$, then the distance in the uniform metric between the distribution function of the standardized number of repetitions of multiplicity $r$ and the distribution function of the standard normal law decreases at a rate of $O(n^{-\delta})$ for any $\delta \in (0,\alpha (32+4\alpha)^{ -1})$ with increasing of segment length $n$.
Keywords:
multiple repetitions, dependent random variables, uniformly strong mixing, normal approximation, convergence rate estimate.
Citation:
V. G. Mikhailov, N. M. Mezhennaya, “The rate of normal approximation for the distribution of the number of multiple repetitions of characters in a stationary random sequence”, Prikl. Diskr. Mat. Suppl., 2022, no. 15, 11–13
Linking options:
https://www.mathnet.ru/eng/pdma568 https://www.mathnet.ru/eng/pdma/y2022/i15/p11
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Abstract page: | 77 | Full-text PDF : | 17 | References: | 10 |
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