Estimate of the bounded Lipschitz metric for sums of weakly dependent random variables

DOI10.1007/BF00966080zbMath0696.60027OpenAlexW1968292778MaRDI QIDQ910807

Jonas Kazys Sunklodas

Publication date: 1989

Published in: Lithuanian Mathematical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00966080

zbMATH Keywords

normal distributionconvergence rate estimatesweakly dependent random variablesprobabilistic metricsbounded Lipschitz functions

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05)

Related Items (5)

On normal approximation of discounted and strongly mixing random variables ⋮ Some estimates in the central limit theorem for \(\varphi\)-mixing random variables ⋮ On the normal approximation of a sum of a random number of independent random variables ⋮ On normal approximation for \(\varphi\)-mixing and \(m\)-dependent random variables ⋮ On normal approximation for strongly mixing random variables

Cites Work

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• \(L_\infty\)-bound for asymptotic normality of weakly dependent summands using Stein's result
• \(L_1\) bounds for asymptotic normality of m-dependent sums using Stein's technique
• The central limit theorem for dependent random variables
• Convergence rates of the strong law for stationary mixing sequences
• Multiple comparisons and sums of dissociated random variables
• The central limit problem for mixing sequences of random variables
• On the strong law of large numbers for a class of stochastic processes

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