Weak laws of large numbers for arrays of rowwise negatively dependent random variables.
Taylor, R.L., Patterson, R.F., Bozorgnia, A. (2001)
Journal of Applied Mathematics and Stochastic Analysis
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Taylor, R.L., Patterson, R.F., Bozorgnia, A. (2001)
Journal of Applied Mathematics and Stochastic Analysis
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Amini, M., Bozorgnia, A. (2000)
Journal of Applied Mathematics and Stochastic Analysis
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Hamadouche, D. (2000)
Portugaliae Mathematica
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Zhu, Meng-Hu (2007)
Discrete Dynamics in Nature and Society
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Yongfeng Wu, Dingcheng Wang (2012)
Applications of Mathematics
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In this paper the authors study the convergence properties for arrays of rowwise pairwise negatively quadrant dependent random variables. The results extend and improve the corresponding theorems of T. C. Hu, R. L. Taylor: On the strong law for arrays and for the bootstrap mean and variance, Int. J. Math. Math. Sci 20 (1997), 375–382.
Paulo Eduardo Oliveira, Charles Suquet (1995)
Commentationes Mathematicae Universitatis Carolinae
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Invariance principle in is studied using signed random measures. This approach to the problem uses an explicit isometry between and a reproducing kernel Hilbert space giving a very convenient setting for the study of compactness and convergence of the sequence of Donsker functions. As an application, we prove a version of the invariance principle in the case of -mixing random variables. Our result is not available in the -setting.