Strong laws of large numbers for arrays of rowwise NA and LNQD random variables

DOI10.1155/2011/708087zbMath1235.60025OpenAlexW2077181162WikidataQ58692056 ScholiaQ58692056MaRDI QIDQ764417

Qunying Wu, Jiang-Feng Wang

Publication date: 13 March 2012

Published in: Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2011/708087

zbMATH Keywords

strong laws of large numbersnegatively associated random variablesnegative quadrant dependent random variables

Mathematics Subject Classification ID

Strong limit theorems (60F15)

Related Items (3)

Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence ⋮ The law of the iterated logarithm for LNQD sequences ⋮ Asymptotic normality and mean consistency for the weighted estimator in nonparametric regression models

Cites Work

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• A note on the almost sure convergence of sums of negatively dependent random variables
• On the strong law for arrays and for the bootstrap mean and variance
• A comparison theorem on moment inequalities between negatively associated and independent random variables
• Negative association of random variables, with applications
• Limiting behaviors of weighted sums for linearly negative quadrant dependent random variables
• A general method to the strong law of large numbers and its applications
• A Berry-Esseen theorem for weakly negatively dependent random variables and its applications
• EXPONENTIAL PROBABILITY INEQUALITY FOR LINEARLY NEGATIVE QUADRANT DEPENDENT RANDOM VARIABLES
• Some Concepts of Dependence
• Probability Inequalities for Sums of Independent Random Variables

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