Complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables and its application to the EV regression model*

IF 0.5 4区数学 Q4 STATISTICS & PROBABILITY

Stochastic Models Pub Date : 2022-09-16 DOI:10.1080/15326349.2022.2112604

Fen Jiang, Miaomiao Wang, Xuejun Wang

引用次数: 0

Abstract

Abstract In this article, we prove the complete q-th moment convergence for the maximum of partial sums of -negatively associated random variables under some general conditions. The results obtained in this article are extensions of previous studies for -negatively associated random variables. In addition, we investigate the strong consistency of the least squares estimator in the simple linear errors-in-variables model based on -negatively associated random variables, and provide some simulations to assess the finite sample performance of the theoretical results.

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负相关随机变量部分和最大值的完全q矩收敛性及其在EV回归模型中的应用*

摘要本文证明了在某些一般条件下，负相关随机变量的部分和的最大值的完全q阶矩收敛性。本文获得的结果是对先前研究负相关随机变量的扩展。此外，我们还研究了基于负相关随机变量的简单线性误差变量模型中最小二乘估计量的强一致性，并提供了一些仿真来评估有限样本理论结果的性能。

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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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.