Equivalent Conditions of Complete Convergence for Weighted Sums of Sequences of Negatively Dependent Random Variables | Zendy

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Equivalent Conditions of Complete Convergence for Weighted Sums of Sequences of Negatively Dependent Random Variables

Author(s) -

Mingle Guo

Publication year - 2012

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2012/425969

Subject(s) - mathematics , truncation (statistics) , convergence (economics) , random variable , moment (physics) , proofs of convergence of random variables , convergence of random variables , statistics , sum of normally distributed random variables , combinatorics , economics , economic growth , physics , classical mechanics

The complete convergence for weighted sums of sequences of negatively dependent random variables is investigated. By applying moment inequality and truncation methods, the equivalent conditions of complete convergence for weighted sums of sequences of negatively dependent random variables are established. These results not only extend the corresponding results obtained by Li et al. (1995), Gut (1993), and Liang (2000) to sequences of negatively dependent random variables, but also improve them

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