A general method to the strong law of large numbers and its applications

A general method to prove the strong law of large numbers is given by using the maximal tail probability. As a result the convergence rate of Sn/n for both positively associated sequences and negatively associated sequences is for any [delta]>1. This result closes to the optimal achievable convergence rate under independent random variables, and improves the rates n-1/3(logn)2/3 and n-1/3(logn)5/3 obtained by Ioannides and Roussas [1999. Exponential inequality for associated random variables. Statist. Probab. Lett. 42, 423-431] and Oliveira [2005. An exponential inequality for associated variables. Statist. Probab. Lett. 73, 189-197], respectively. In this sense the proposed general method may be more effective than its peers provided by Fazekas and Klesov [2001. A general approach to the strong law of large numbers. Theory Probab. Appl. 45(3), 436-449] and Ioannides and Roussas [1999. Exponential inequality for associated random variables. Statist. Probab. Lett. 42, 423-431].