Moment Convergence for Maximum Weighted Sums of NSD Random Arrays and Application
This paper mainly investigates the moment convergence for the maximum weighted sums of an array of NSD random variables by using the maximum moment inequality of NSD random variables.The corresponding theorems improve and extend the existing result for AANA random variables.Moreover,as an application of the main results,the moment consistency and the weak consistency of the weighted esti-mator in nonparametric regression model are further investigated.
moment convergencemaximum weighted sumsNSD random arraysnonparametric regression modelmoment consistency
NETL
NSTL
万方数据
维普
