A lower bound for the tail probability of partial maxima of dependent random variables and applications

DOI10.1007/s12044-021-00607-wzbMath1470.60093OpenAlexW3165056720MaRDI QIDQ2024784

Fakhreddine Boukhari

Publication date: 4 May 2021

Published in: Proceedings of the Indian Academy of Sciences. Mathematical Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s12044-021-00607-w

zbMATH Keywords

complete convergencelimit theoremsAANA sequencesBaum-Katz strong lawKolmogorov-Feller weak law

Mathematics Subject Classification ID

Sums of independent random variables; random walks (60G50) Strong limit theorems (60F15)

Related Items (5)

Limit theorems for dependent random variables with infinite means ⋮ A remark on the Kolmogorov-Feller weak law of large numbers ⋮ Weak law of large numbers and complete convergence for general dependent sequences ⋮ On a Spitzer-type law of large numbers for partial sums of m-negatively associated random variables ⋮ On a weak law of large numbers with regularly varying normalizing sequences

Cites Work

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• Marcinkiewicz-Zygmund type strong law of large numbers for pairwise i.i.d. random variables
• An extension of the Kolmogorov-Feller weak law of large numbers with an application to the St. Petersburg game
• Rosenthal type inequalities for asymptotically almost negatively associated random variables and applications
• Iterated logarithm laws for asymmetric random variables barely with or without finite mean
• Convergence rates and r-quick versions of the strong law for stationary mixing sequences
• Negative association of random variables, with applications
• Extensions of the strong law of large numbers of Marcinkiewicz and Zygmund for dependent variables
• The Marcinkiewics-Zygmund strong law of large numbers for dependent random variables
• Strong convergence for sequences of asymptotically almost negatively associated random variables
• Convergence rates of the strong law for stationary mixing sequences
• Probability: A Graduate Course
• Weak laws of large numbers for maximal weighted sums of random variables
• A Generalization of Weak Law of Large Numbers
• On an Extension of the Weak Law of Large Numbers of Kolmogorov and Feller
• Convergence Rates in the Law of Large Numbers
• Association of Random Variables, with Applications
• Complete Convergence and the Law of Large Numbers
• On a Theorem of Hsu and Robbins

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