Tail approximations of integrals of Gaussian random fields

Tail approximations of integrals of Gaussian random fields
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高斯随机场积分的​​尾部近似

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发表时间:
2010
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通讯作者:
Jingcheng Liu
Jingcheng Liu
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作者:
Jingcheng Liu

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本文对生活在紧致d维Jordan可测集T上的齐次光滑高斯随机场f,给出了P(τ Tef(t)dt > B)在B → ∞时的渐近逼近.高斯随机场指数的积分是空间点过程、投资组合风险分析、资产定价等许多一般模型的重要随机变量。 分析技术包括两个步骤:1。在一个依赖于B的小域上估计尾概率P(t_ref(t)dt > B),其中当B → ∞时,mes(t_ref(t))→ 0,mes(t_ref(t))是勒贝格测度; 2.在适当选择的条件下,我们证明了P(<$Tef(t)dt > B)=(1 + o(1))mes(T)mes−1(<$)P(<$Tef(t)dt > B)。
This paper develops asymptotic approximations of P(∫Tef(t) dt > b) as b → ∞ for a homogeneous smooth Gaussian random field, f, living on a compact d-dimensional Jordan measurable set T. The integral of an exponent of a Gaussian random field is an important random variable for many generic models in spatial point processes, portfolio risk analysis, asset pricing and so forth. The analysis technique consists of two steps: 1. evaluate the tail probability P(∫Ξef(t) dt > b) over a small domain Ξ depending on b, where mes(Ξ) → 0 as b → ∞ and mes(⋅) is the Lebesgue measure; 2. with Ξ appropriately chosen, we show that P(∫Tef(t) dt > b) = (1 + o(1)) mes(T) mes−1(Ξ) P(∫Ξef(t) dt > b).