Small deviations of smooth stationary Gaussian processes
Small deviations of smooth stationary Gaussian processes
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平滑平稳高斯过程的小偏差
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
V. Zanten
中科院分区：
文献类型：
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作者：
F. Aurzada;I. Ibragimov;M. Lifshits;V. Zanten
研究了一类在贝叶斯统计推断中起重要作用的平稳高斯过程的小偏差概率。我们的计算是基于适当的修改熵的方法，由于Kuelbs，李，林德以及经典结果的熵类解析函数。他们还涉及Tsirelson的小偏差的上限，并揭示了一些关于该估计的清晰度的限制。
We investigate the small deviation probabilities of a class of very smooth stationary Gaussian processes playing an important role in Bayesian statistical inference. Our calculations are based on the appropriate modification of the entropy method due to Kuelbs, Li, and Linde as well as on classical results about the entropy of classes of analytic functions. They also involve Tsirelson's upper bound for small deviations and shed some light on the limits of sharpness for that estimate.