STABLE LIMITS FOR ASSOCIATED RANDOM-VARIABLES

• 成果类型: Article
• 署名作者: DABROWSKI, AR; JAKUBOWSKI, A
• 署名单位: Nicolaus Copernicus University
• 刊物名称: ANNALS OF PROBABILITY
• ISSN/ISSBN: 0091-1798
• DOI: 10.1214/aop/1176988845
• 发表日期: 1994
• 页码: 1-16
• 关键词: iterated logarithm; functional law; random vectors; THEOREM; SEQUENCES

摘要

We consider a stationary sequence of associated real random variables and state conditions which guarantee that partial sums of this sequence, when properly normalized, converge in distribution to a stable, non-Gaussian limit. Limit theorems for jointly stable and associated random variables are investigated in detail. In the general case we assume that finite-dimensional distributions belong to the domain of attraction of multidimensional strictly stable laws and that there is a bound on the positive dependence given by finiteness of an analog to the lag covariance series.