A Hájek-Rényi type inequality and its applications.
Tómács, Tibor, Líbor, Zsuzsanna (2006)
Annales Mathematicae et Informaticae
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Displaying similar documents to “Almost sure central limit theorem for product of partial sums of strongly mixing random variables.”
A Hájek-Rényi type inequality and its applications.
Almost sure central limit theorems for strongly mixing and associated random variables.
Gonchigdanzan, Khurelbaatar (2002)
International Journal of Mathematics and Mathematical Sciences
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Complete convergence for maximal sums of negatively associated random variables.
Kruglov, Victor M. (2010)
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Complete convergence for negatively dependent sequences of random variables.
Wu, Qunying (2010)
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Wu, Qunying (2010)
Journal of Inequalities and Applications [electronic only]
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A note on almost sure central limit theorem in the joint version for the maxima and sums.
Zang, Qing-Pei, Wang, Zhi-Xiang, Fu, Ke-Ang (2010)
Journal of Inequalities and Applications [electronic only]
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Complete convergence for weighted sums of sequences of negatively dependent random variables.
Wu, Qunying (2011)
Journal of Probability and Statistics
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Hajek-Renyi-type inequality for some nonmonotonic functions of associated random variables.
Dewan, Isha, Prakasa Rao, B.L.S. (2006)
Journal of Inequalities and Applications [electronic only]
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Strong laws of large numbers for -valued random fields.
Lagodowski, Zbigniew A. (2009)
Discrete Dynamics in Nature and Society
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Convergence of stopped sums of weakly dependent random variables.
Peligrad, Magda (1999)
Electronic Journal of Probability [electronic only]
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A probabilistic approach to the asymptotics of the length of the longest alternating subsequence.
Houdré, Christian, Restrepo, Ricardo (2010)
The Electronic Journal of Combinatorics [electronic only]
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Central limit theorem for sampled sums of dependent random variables
Nadine Guillotin-Plantard, Clémentine Prieur (2010)
ESAIM: Probability and Statistics
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We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to dependent random variables sampled by a -valued transient random walk. This extends the results obtained by [N. Guillotin-Plantard and D. Schneider, (2003) 477–497]. An application to parametric estimation by random sampling is also provided.