Abstract
A new condition for a weak dependence of random variables is determined, which makes it possible to extend limit theorems for independent random variables to the case of weakly dependent variables with the preservation of the convergence rate. An example of a sequence of random variables satisfying the new weak dependence condition is given.
Similar content being viewed by others
References
M. Rosenblatt, “A central limit theorem and a strong mixing condition,” Proc. Nat. Acad. Sci. USA 42(1), 43–47 (1956).
I. A. Ibragimov and Yu. V. Linnik, Independent and Stationary Sequences of Random Variables (Nauka, Moscow, 1965) [in Russian].
J. R. Blum, D. L. Hanson, and L. H. Koopmans, “On the strong law of large numbers for a class of stochastic processes,” Z. Wahrsch. Verw. Gebiete. 2(1), 1–11 (1963).
M. Loève, Probability Theory (D. van Nostrand, Princeton, N.J., 1060; Inostrannaya Literatura, Moscow, 1962).
M. Iosifescu, “Recent advances in mixing sequences of random variables,” in Third International Summer School on Probability Theory and Mathematical Statistics, Varna, Bulgaria, 1978 (Bulgarian Acad. Sci., Sofia, 1980), pp. 111–138.
Author information
Authors and Affiliations
Corresponding author
Additional information
Original Russian Text © V.T. Dubrovin, 2013, published in Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 2013, Vol. 155, No. 4, pp. 40–47.
Rights and permissions
About this article
Cite this article
Dubrovin, V.T. Convergence rate in limit theorems for weakly dependent random values. Lobachevskii J Math 35, 390–396 (2014). https://doi.org/10.1134/S1995080214040039
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1995080214040039