历史相关随机线性递归的分布尾

IF 0.5 4区数学 Q4 STATISTICS & PROBABILITY

Stochastic Models Pub Date : 2022-01-11 DOI:10.1080/15326349.2021.2003712

A. Roitershtein, Zirou Zhou

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引用次数: 1

摘要

本文采用Clifford和Stirzaker提出的连续时间框架，考虑一个历史相关的随机线性递归。通常，研究历史依赖过程的主要兴趣对象是其第一和第二时刻的演化和渐近行为。我们采用Clifford和Stirzaker开发的方法，利用正则变分状态下的尾的渐近结构与Clifford和Stirzaker引入的一类模型中矩的线性结构之间的某种亲缘关系，来研究过程的分布尾的演化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Distribution tails of a history-dependent random linear recursion

Abstract We consider a history-dependent random linear recursion, adapting a continuous-time framework introduced by Clifford and Stirzaker. Typically, the main object of interest in the study of history-dependent processes is the evolution and asymptotic behavior of their first and second moments. We apply the methodology developed by Clifford and Stirzaker to study the evolution of distribution tails of the process by utilizing a certain affinity between the asymptotic structure of the tails in a regular variation regime and a linear structure of moments in the class of models introduced by Clifford and Stirzaker.

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来源期刊

Stochastic Models 数学-统计学与概率论

CiteScore

1.30

自引率

14.30%

发文量

审稿时长

>12 weeks

期刊介绍： Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.