负超可加相依随机变量Sung型加权和的完全f矩收敛性

Complete f-Moment Convergence for Sung’s Type Weighted Sums of Negatively Superadditive Dependent Random Variables

  • 摘要: 利用负超可加相依随机阵列(NSD)的M-Z型不等式和Rosenthal型不等式及截尾的方法,探讨了NSD随机变量Sung型随机加权和的完全f矩收敛性,在一些合适的条件下,获得了NSD随机变量Sung型随机加权和完全f矩收敛性的一些一般结果,推广并改进了相关文献已有结论。最后,给出了基于NSD误差的非参数回归模型中随机加权和估计的完全相合性例子作为其应用。

     

    Abstract: In this paper, by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent (NSD) random arrays and truncated method, the complete f-moment convergence of NSD random variables is studied. We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions. As an application, the complete consistency for the randomly weighted estimator is presented in a nonparametric regression model based on NSD errors.

     

/

返回文章
返回