arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1105.6129math.PR
收藏

无穷方差线性过程的中心极限定理

Central Limit Theorem for Linear Processes with Infinite Variance

Magda Peligrad, Hailin Sang

摘要:

本文讨论了如下经典问题:给定一个正态律吸引区域中的同分布随机变量序列,其线性过程是否满足中心极限定理?本文研究了几类相依随机变量的这一问题。对于独立同分布的随机变量,我们证明了线性过程的中心极限定理等价于这样一个事实,即变量是在吸引区域的一个正常的法律,以这种方式回答了一个公开的问题在文献中。这项研究的动机也是在经济应用中产生的模型,往往创新具有无限的方差,系数不是绝对可求和的,创新是依赖的。

英文摘要:

This paper addresses the following classical question: giving a sequence of identically distributed random variables in the domain of attraction of a normal law, does the associated linear process satisfy the central limit theorem? We study the question for several classes of dependent random variables. For independent and identically distributed random variables we show that the central limit theorem for the linear process is equivalent to the fact that the variables are in the domain of attraction of a normal law, answering in this way an open problem in the literature. The study is also motivated by models arising in economic applications where often the innovations have infinite variance, coefficients are not absolutely summable, and the innovations are dependent.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑