Supremum Distribution of Weighted Sum of Random Processes from Orlicz Spaces of Exponential Type with Continuous Deviation

IF 0.6 Q4 STATISTICS & PROBABILITY
Dmytro Tykhonenko, R. Yamnenko
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引用次数: 0

Abstract

The paper studies distribution of sum of random processes from Orlicz spaces of exponential type weighted by continuous functions, in particular, processes from spaces Subϕ (Ω), SSubϕ (Ω) and class V (ϕ, ψ) are considered. Such spaces and classes of random variables and corresponding stochastic processes provide generalizations of Gaussian and sub-Gaussian random variables and processes and are important for various applications, for example, in queuing theory and financial mathematics. We derive the estimates for the distribution of supremum of weighted sum of such processes deviated by a continuous monotone function using the entropy method. As examples, weighted sum of Wiener and weighted sum of fractional Brownian motion processes with different Hurst indices from classes V (ϕ, ψ) are considered. Corresponding estimates of the probability of exceeding by trajectories of such weighted sums a positive level determined by a linear function are obtained. In the insurance risk theory, such aproblem arises during estimating a ruin probability of the corresponding risk process with a constant premium income, and in the communications theory, it appears for the buffer overflow probability for a single server with a constant service rate.
具有连续偏差的指数型Orlicz空间随机过程加权和的最大分布
本文研究了连续函数加权指数型Orlicz空间中随机过程和的分布,特别考虑了空间subφ (Ω)、ssubφ (Ω)和类V (φ, ψ)中的过程。这些随机变量的空间和类别以及相应的随机过程提供了高斯和亚高斯随机变量和过程的推广,对于各种应用都很重要,例如在排队论和金融数学中。我们用熵的方法得到了这类过程被连续单调函数偏离的加权和的上极值分布的估计。作为例子,考虑了V (φ, ψ)类中具有不同Hurst指标的Wiener加权和分数阶布朗运动过程的加权和。得到了这些加权和的轨迹超过由线性函数决定的正水平的概率的相应估计。在保险风险理论中,在保费收入不变的情况下,对相应风险过程的破产概率进行估计时,会出现这样的问题;在通信理论中,在服务速率不变的情况下,对单个服务器的缓冲区溢出概率进行估计时,会出现这样的问题。
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来源期刊
Austrian Journal of Statistics
Austrian Journal of Statistics STATISTICS & PROBABILITY-
CiteScore
1.10
自引率
0.00%
发文量
30
审稿时长
24 weeks
期刊介绍: The Austrian Journal of Statistics is an open-access journal (without any fees) with a long history and is published approximately quarterly by the Austrian Statistical Society. Its general objective is to promote and extend the use of statistical methods in all kind of theoretical and applied disciplines. The Austrian Journal of Statistics is indexed in many data bases, such as Scopus (by Elsevier), Web of Science - ESCI by Clarivate Analytics (formely Thompson & Reuters), DOAJ, Scimago, and many more. The current estimated impact factor (via Publish or Perish) is 0.775, see HERE, or even more indices HERE. Austrian Journal of Statistics ISNN number is 1026597X Original papers and review articles in English will be published in the Austrian Journal of Statistics if judged consistently with these general aims. All papers will be refereed. Special topics sections will appear from time to time. Each section will have as a theme a specialized area of statistical application, theory, or methodology. Technical notes or problems for considerations under Shorter Communications are also invited. A special section is reserved for book reviews.
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