On normal approximation of discounted and strongly mixing random variables |
| |
Authors: | J. Sunklodas |
| |
Affiliation: | (1) Institute of Mathematics and Informatics, Akademijos 4, LT-08663 Vilnius;(2) Vilnius Gediminas Technical University, Saulétekio 11, LT-10223 Vilnius, Lithuania |
| |
Abstract: | We estimate the difference for bounded functions h: ℝ → ℝ satisfying the Lipschitz condition, where Z v = B v −1 ∑ i=0 ∞ v i X i and with discount factor ν such that 0 < ν < 1. Here {X n , n ≥ 0} is a sequence of strongly mixing random variables with , and N is a standard normal random variable. In a particular case, the obtained upper bounds are of order O((1 − ν)1/2). Published in Lietuvos Matematikos Rinkinys, Vol. 47, No. 3, pp. 399–409, July–September, 2007. The research was partially supported by the Lithuanian State Science and Studies Foundation, grant No. T-15/07. |
| |
Keywords: | discounted central limit theorem strong mixing condition Lipschitz condition Stein’ s method |
本文献已被 SpringerLink 等数据库收录! |
|