Communications in Statistics - Theory and Methods | 2019
A strong law of large number for negatively dependent and non identical distributed random variables in the framework of sublinear expectation
Abstract
Abstract In this article, in the framework of sublinear expectation initiated by Peng, we derive a strong law of large numbers (SLLN) for negatively dependent and non identical distributed random variables. This result includes and extends some existing results. Furthermore, we give two examples of our result for applications.