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arXiv 1606.01072math.PR
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相关平稳高斯序列和的小偏差

Small deviations of sums of correlated stationary Gaussian sequences

Frank Aurzada, Mikhail Lifshits

摘要:

研究了平稳高斯序列和的小偏差概率。对于常边界和边界趋于零的情形,我们得到了相当一般的结果。对于边界趋于无穷大的情形,我们把注意力集中在分数布朗运动(FBM)的离散模拟上。事实证明,SDP的下界可以转移到离散时间设置下,通常的假设,意味着弱收敛,而相应的上界的转移必然需要更深入的知识的频谱结构的基础平稳序列。

英文摘要:

We consider the small deviation probabilities (SDP) for sums of stationary Gaussian sequences. For the cases of constant boundaries and boundaries tending to zero, we obtain quite general results. For the case of the boundaries tending to infinity, we focus our attention on the discrete analogs of the fractional Brownian motion (FBM). It turns out that the lower bounds for the SDP can be transferred from the well studied FBM caseto the discrete time setting under the usual assumptions that imply weak convergence while the transfer of the corresponding upper bounds necessarily requires a deeper knowledge of the spectral structure of the underlying stationary sequence.

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