数学季刊 >

2014 , Vol. 29 >Issue 2: 195 - 202

DOI: https://doi.org/10.13371/j.cnki.chin.q.j.m.2014.02.006

END随机变量的概率不等式及其应用

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  • School of Mathematics and Computational Science, Fuyang Teacher’s College
TANG Xiao-feng(1978-), male, native of Fuyang, Anhui, a lecturer of Fuyang Teacher's College, M.S.D., engages in probability limit theorem.

收稿日期: 2012-06-08

  网络出版日期: 2020-12-01

基金资助

Supported by the Project of the Feature Specialty of China(TS11496)； Supported by the Scientific Research Projects of Fuyang Teacher’s College(2009FSKJ09)；

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Probability Inequalities for Extended Negatively Dependent Random Variables and Their Applications

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  • School of Mathematics and Computational Science, Fuyang Teacher’s College
TANG Xiao-feng(1978-), male, native of Fuyang, Anhui, a lecturer of Fuyang Teacher's College, M.S.D., engages in probability limit theorem.

Received date: 2012-06-08

  Online published: 2020-12-01

Supported by

Supported by the Project of the Feature Specialty of China(TS11496)； Supported by the Scientific Research Projects of Fuyang Teacher’s College(2009FSKJ09)；

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摘要

Some probability inequalities are established for extended negatively dependent（END） random variables. The inequalities extend some corresponding ones for negatively associated random variables and negatively orthant dependent random variables. By using these probability inequalities, we further study the complete convergence for END random variables. We also obtain the convergence rate O（n-1/2ln1/2n） for the strong law of large numbers, which generalizes and improves the corresponding ones for some known results. 

关键词： extended negatively dependent sequence; negatively orthant dependent sequence; probability inequality; complete convergence

本文引用格式

唐小峰 . END随机变量的概率不等式及其应用[J]. 数学季刊, 2014 , 29(2) : 195 -202 . DOI: 10.13371/j.cnki.chin.q.j.m.2014.02.006

Abstract

Some probability inequalities are established for extended negatively dependent（END） random variables. The inequalities extend some corresponding ones for negatively associated random variables and negatively orthant dependent random variables. By using these probability inequalities, we further study the complete convergence for END random variables. We also obtain the convergence rate O（n-1/2ln1/2n） for the strong law of large numbers, which generalizes and improves the corresponding ones for some known results. 

Key words： extended negatively dependent sequence; negatively orthant dependent sequence; probability inequality; complete convergence

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