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Acta Mathematica Sinica, English Series

, Volume 34, Issue 10, pp 1501–1516 | Cite as

Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables

  • Ji Gao Yan
Article
  • 35 Downloads

Abstract

In this paper, the complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables are investigated. Some sufficient conditions for the convergence are provided. In addition, the Marcinkiewicz–Zygmund type strong law of large numbers for weighted sums of extended negatively dependent random variables is obtained. The results obtained in the article extend the corresponding ones for independent random variables and some dependent random variables.

Keywords

Extended negatively dependent complete convergence complete moment convergence maximal weighted sums strong law of large numbers 

MR(2010) Subject Classification

60F15 

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Copyright information

© Institute of Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Chinese Mathematical Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mathematical SciencesSoochow UniversitySuzhouPR China
  2. 2.C.A.S.E.-Center for Applied Statistics and EconomicsHumboldt-Universität zu BerlinBerlinGermany

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