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On complete and complete moment convergence for weighted sums of ANA random variables and applications

机译:关于ANA随机变量和和的加权和的完全和完全矩收敛

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摘要

In this article, the complete convergence and complete moment convergence for weighted sums of asymptotically negatively associated (ANA, for short) random variables are studied. Several sufficient conditions of the complete convergence and complete moment convergence for weighted sums of ANA random variables are presented. As an application, the complete consistency for the weighted estimator in a nonparametric regression model based on ANA random errors is established by using the complete convergence that we established. We also give a simulation to verify the validity of the theoretical result.
机译:在本文中,研究了渐近负相关(ANA)随机变量的加权和的完全收敛和完全矩收敛。给出了ANA随机变量加权和的完全收敛和完全矩收敛的几个充分条件。作为应用程序,使用我们建立的完全收敛性,可以建立基于ANA随机误差的非参数回归模型中加权估计量的完全一致性。我们还进行了仿真,以验证理论结果的有效性。

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