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 , 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 |
本文献已被 SpringerLink 等数据库收录! |
|