On Berman Functions

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY
Krzysztof Dȩbicki, Enkelejd Hashorva, Zbigniew Michna
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引用次数: 0

Abstract

Let \(Z(t)= \exp \left( \sqrt{ 2} B_H(t)- \left|t \right|^{2H}\right) , t\in \mathbb {R}\) with \(B_H(t),t\in \mathbb {R}\) a standard fractional Brownian motion (fBm) with Hurst parameter \(H \in (0,1]\) and define for x non-negative the Berman function

$$\begin{aligned} \mathcal {B}_{Z}(x)= \mathbb {E} \left\{ \frac{ \mathbb {I} \{ \epsilon _0(RZ) > x\}}{ \epsilon _0(RZ)}\right\} \in (0,\infty ), \end{aligned}$$

where the random variable R independent of Z has survival function \(1/x,x\geqslant 1\) and

$$\begin{aligned} \epsilon _0(RZ) = \int _{\mathbb {R}} \mathbb {I}{\left\{ RZ(t)> 1\right\} }{dt} . \end{aligned}$$

In this paper we consider a general random field (rf) Z that is a spectral rf of some stationary max-stable rf X and derive the properties of the corresponding Berman functions. In particular, we show that Berman functions can be approximated by the corresponding discrete ones and derive interesting representations of those functions which are of interest for Monte Carlo simulations presented in this article.

Abstract Image

关于伯曼函数
让 \(Z(t)= \exp \left( \sqrt{ 2} B_H(t)- \left|t \right|^{2H}\right) , t\in \mathbb {R}\) with \(B_H(t)、t 在 (mathbb {R}\)是一个标准的分数布朗运动(fBm),具有赫斯特参数 (H 在 (0,1]\),并定义 x 为非负的伯曼函数 $$\begin{aligned}\mathcal {B}_{Z}(x)= \mathbb {E}\Left (左) (frac (右) (mathbb {I}\{ \epsilon _0(RZ) > x\}{ \epsilon _0(RZ)}\right\}\in (0,\infty ), \end{aligned}$$其中独立于Z的随机变量R具有生存函数(1/x,x\geqslant 1\) and $$\begin{aligned}\epsilon _0(RZ) = \int _{mathbb {R}}\RZ(t)> 1\right\} }{dt} .}{dt} .\end{aligned}$$ 在本文中,我们考虑了一个一般随机场(rf)Z,它是某个静态最大稳定随机场 X 的谱随机场,并推导了相应伯曼函数的性质。特别是,我们证明伯曼函数可以用相应的离散函数来近似,并推导出这些函数的有趣表示形式,这些表示形式对本文介绍的蒙特卡罗模拟很有意义。
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
58
审稿时长
6-12 weeks
期刊介绍: Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics. The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests: -Algorithms- Approximations- Asymptotic Approximations & Expansions- Combinatorial & Geometric Probability- Communication Networks- Extreme Value Theory- Finance- Image Analysis- Inequalities- Information Theory- Mathematical Physics- Molecular Biology- Monte Carlo Methods- Order Statistics- Queuing Theory- Reliability Theory- Stochastic Processes
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