WOD随机变量序列移动平均过程的收敛性

Convergence of Moving Average Processes for WOD Random Variable

WOD(widely orthant dependent)随机变量序列是一类宽泛的相依随机变量序列。主要研究由WOD随机变量序列生成的移动平均过程的收敛性,利用WOD序列的Rosenthal型矩不等式和Rademacher-Menshov型最大值矩不等式,获得了移动平均过程部分和最大值的矩完全收敛性和完全收敛性,结论推广了相依变量序列生成移动平均过程的结果。

WOD(widely orthant dependent)is a sequence of random variables,which has a broad dependency.The paper mainly investigates the convergence of the moving average processes,which is generated by WOD random variables.By using the Rosenthaltype moment inequality and the Rademacher-Menshov type maximum moment inequality of the WOD random variables,moment complete convergence and complete convergence of the maximal partial sums for moving average processes are obtained.The results in this article extend and improve the results of the moving average process.