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arXiv 1807.09707math.PR
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Breuer-Major定理中的全变差估计

Total variation estimates in the Breuer-Major theorem

David Nualart, Hongjuan Zhou

摘要:

本文在Breuer-Major定理的框架下,在假定函数具有某些光滑性质的情况下,给出了全变差距离的收敛速度的估计.结果证明了应用新的界限之间的全变差的随机变量表示为一个分歧和一个标准的高斯随机变量,这是由Malliavin演算和Stein的方法相结合的技术。通过在Hermite多项式展开式上引入一个移位算子,建立了高斯序列的泛函的散度表示。给出了分数阶布朗运动幂变分的渐近性态和利用幂变分估计Hurst参数的一些应用。

英文摘要:

This paper provides estimates for the convergence rate of the total variation distance in the framework of the Breuer-Major theorem, assuming some smoothness properties of the underlying function. The results are proved by applying new bounds for the total variation distance between a random variable expressed as a divergence and a standard Gaussian random variable, which are derived by a combination of techniques of Malliavin calculus and Stein's method. The representation of a functional of a Gaussian sequence as a divergence is established by introducing a shift operator on the expansion in Hermite polynomials. Some applications to the asymptotic behavior of power variations of the fractional Brownian motions and to the estimation of the Hurst parameter using power variations are presented.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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