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On Normal Approximation for Strongly Mixing Random Variables
Authors:J. Sunklodas
Affiliation:(1) Institute of Mathematics and Informatics, Akademijos 4, 08663 Vilnius, Lithuania
Abstract:In this paper, we estimate the difference $vert mathbb{E}h(Z_{n})-mathbb{E}h(N)vert $ , where Z n is the sum of n centered and normalized random variables (without the stationarity assumption) satisfying the strong mixing condition, N is a standard normal random variable, and h:ℝ→ℝ is a Lipschitz function. In particular cases, the obtained upper bounds are of order O(n −1/2). The research was partially supported by the Lithuanian State Science and Studies Foundation, grant No. T-10/06.
Keywords:Normal approximation  Bounded Lipschitz metric  Strong mixing condition  Weakly dependent random variables  Stein’  s method
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