Title :
Some Limit Theorems for Arbitrary Stochastic Sequence
Author :
Wang, Xiaosheng ; Guo, Haiying
Author_Institution :
Coll. of Sci., Hebei Univ. of Eng., Handan, China
Abstract :
In order to provide the general law which random variables satisfy the strong stability, the sufficient conditions of strong convergence for arbitrary stochastic sequence considered on certain subsets of the sample space are presented. By using Doob´s martingale convergence theorem and stopping time, this paper obtains three strong limit theorems for arbitrary stochastic sequence. Chow´s strong law of large numbers for martingale-difference sequence and Lo´eve´s strong limit theorem on independent random variables are corollaries of the main results.
Keywords :
random processes; stochastic processes; Loeve strong limit theorem; arbitrary stochastic sequence; martingale convergence theorem; martingale-difference sequence; random variables; Convergence; Educational institutions; Random variables; Stability; Stochastic processes; Sufficient conditions; Tin; Zinc; Strong law of large numbers; arbitrary stochastic sequence; martingale;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.481