Almost sure central limit theorems for strongly mixing and associated random variables.
Gonchigdanzan, Khurelbaatar (2002)
International Journal of Mathematics and Mathematical Sciences
Similarity:
The search session has expired. Please query the service again.
Displaying similar documents to “A note on almost sure central limit theorem in the joint version for the maxima and sums.”
Almost sure central limit theorems for strongly mixing and associated random variables.
Almost sure central limit theorem for product of partial sums of strongly mixing random variables.
Ye, Daxiang, Wu, Qunying (2011)
Journal of Inequalities and Applications [electronic only]
Similarity:
Precise rates in log laws for NA sequences.
Zhao, Yuexu (2007)
Discrete Dynamics in Nature and Society
Similarity:
An almost sure limit theorem for -mixing random fields.
Tómács, Tibor (2008)
Annales Mathematicae et Informaticae
Similarity:
Complete convergence for weighted sums of sequences of negatively dependent random variables.
Wu, Qunying (2011)
Journal of Probability and Statistics
Similarity:
Chover-type laws of the iterated logarithm for weighted sums of -mixing sequences.
Cai, Guang-Hui (2006)
Journal of Applied Mathematics and Stochastic Analysis
Similarity:
A Hájek-Rényi type inequality and its applications.
Tómács, Tibor, Líbor, Zsuzsanna (2006)
Annales Mathematicae et Informaticae
Similarity:
An almost sure limit theorem for the maxima of strongly dependent Gaussian sequences.
Lin, Fuming (2009)
Electronic Communications in Probability [electronic only]
Similarity:
A note on strong convergence of sums of dependent random variables.
Hu, Tien-Chung, Weber, Neville C. (2009)
Journal of Probability and Statistics
Similarity:
Strong approximation for mixing sequences with infinite variance.
Balan, Raluca, Zamfirescu, Ingrid-Mona (2006)
Electronic Communications in Probability [electronic only]
Similarity:
A strong invariance principle for negatively associated random fields
Guang-hui Cai (2011)
Czechoslovak Mathematical Journal
Similarity:
In this paper we obtain a strong invariance principle for negatively associated random fields, under the assumptions that the field has a finite th moment and the covariance coefficient exponentially decreases to . The main tools are the Berkes-Morrow multi-parameter blocking technique and the Csörgő-Révész quantile transform method.