NSD序列加权和的中心极限定理及其在EV回归模型中的应用

摘要

基于负超可加相依(简称为NSD )随机序列的性质及其一些不等式，利用随机变量的截断方法建立了NSD 随机序列加权和的中心极限定理，从而推广了负相协NA 随机序列的相应结论。并将其应用到变系数EV 回归模型，得到了未知参数LS 估计的渐近正态性。%By using the properties and some inequalities of negatively superadditive dependent (NSD) random sequences and the trunkated method, a central limit theorem for weighted sums of NSD random sequences is discussed , which generalizes and improves corresponding conclusions for negatively associated (NA) random sequences. As an application, the asymptotic normality of LS estimators of the unknown parameters in the variable coefficients EV regression model with NSD errors is obtained as well, which generalizes corresponding conclusions of negatively associated random sequences.