On the strong convergence for weighted sums of negatively superadditive dependent random variables
نویسندگان
چکیده
منابع مشابه
Strong Convergence of Weighted Sums for Negatively Orthant Dependent Random Variables
We discuss in this paper the strong convergence for weighted sums of negatively orthant dependent (NOD) random variables by generalized Gaussian techniques. As a corollary, a Cesaro law of large numbers of i.i.d. random variables is extended in NOD setting by generalized Gaussian techniques.
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In this article, some strong convergence results for weighted sums of negatively superadditive dependent random variables are studied without assumption of identical distribution. The results not only generalize the corresponding ones of Cai (Metrika 68:323-331, 2008) and Sung (Stat. Pap. 52:447-454, 2011), but also extend and improve the corresponding one of Chen and Sung (Stat. Probab. Lett. ...
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متن کاملstrong convergence of weighted sums for negatively orthant dependent random variables
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ژورنال
عنوان ژورنال: Journal of Inequalities and Applications
سال: 2017
ISSN: 1029-242X
DOI: 10.1186/s13660-017-1530-9