Strong convergence results for arrays of rowwise pairwise NQD random variables

DOI10.1186/1029-242X-2013-102zbMath1284.60065WikidataQ59301641 ScholiaQ59301641MaRDI QIDQ2636706

Xiaofeng Tang

Publication date: 31 January 2014

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

zbMATH Keywords

complete convergenceweighted sumsarrays of rowwise pairwise NQD random variables

Mathematics Subject Classification ID

Strong limit theorems (60F15)

Related Items (9)

Complete convergence for arrays of row-wise negatively superadditive-dependent random variables and its applications ⋮ Almost everywhere convergence for sequences of pairwise NQD random variables ⋮ On the strong convergence and complete convergence for pairwise NQD random variables ⋮ On the strong convergence for weighted sums of negatively associated random variables ⋮ Complete consistency of the estimator of nonparametric regression model under ND sequence ⋮ General results of complete convergence and complete moment convergence for weighted sums of some class of random variables ⋮ On complete convergence for weighted sums of \(\rho^*\)-mixing random variables ⋮ A note on the rate of strong convergence for weighted sums of arrays of rowwise negatively orthant dependent random variables ⋮ Applications of the Rosenthal-type inequality for negatively superadditive dependent random variables

Cites Work

• An exponential inequality for a NOD sequence and a strong law of large numbers
• A note on the almost sure convergence of sums of negatively dependent random variables
• Complete convergence for arrays
• A comparison theorem on moment inequalities between negatively associated and independent random variables
• Negative association of random variables, with applications
• Maximal inequalities and an invariance principle for a class of weakly dependent random variables
• Exponential inequalities and inverse moment for NOD sequence
• Convergence of weighted averages of independent random variables
• Some Concepts of Dependence
• Complete Convergence and the Law of Large Numbers

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