数理科学

NSD随机变量序列下半参数回归模型估计的相合性

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  • 巢湖学院 数学与统计学院,安徽 巢湖 238024
张玉(1989—),男,安徽合肥人,巢湖学院数学与统计学院讲师,主要从事概率极限理论研究。

收稿日期: 2022-03-25

  网络出版日期: 2022-09-05

基金资助

巢湖学院校级项目(项目编号:XLY-202104)

Consistency Estimation Lower Semiparametric Regression Model for NSD Random Variable Sequence

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  • School of Mathematics and Statistics, Chaohu University, Chaohu Anhui 238024

Received date: 2022-03-25

  Online published: 2022-09-05

摘要

相依随机变量序列自从出现以后得到了学者们广泛的研究,回归模型在实际应用中有着重要的作用,研究NSD(negatively superadditive dependent)相依随机变量序列下半参数回归模型估计的相合性既扩展了相依随机变量性质的应用,又丰富了半参数回归模型估计相关理论。研究采用随机变量尾截技术结合NSD随机变量自身性质得出NSD随机变量序列下半参数回归模型估计的相合性。

本文引用格式

张玉 . NSD随机变量序列下半参数回归模型估计的相合性[J]. 巢湖学院学报, 2022 , 24(3) : 47 -51 . DOI: 10.12152/j.issn.1672-2868.2022.03.006

Abstract

The sequence of dependent random variables has been widely studied by scholars since its emergence, and the regression model plays an important role in practical application. Studying the consistency of the estimation of lower semiparametric regression model under the NSD (negatively superadditive dependent) dependent random variables sequence not only expands the application of the properties of dependent random variables, but also enriches the estimation theory of semiparametric regression mode. In this paper, the consistency of the estimation of the lower semi parametric regression model of NSD random variable sequence is obtained by using the tail cut technique of random variables and the properties of NSD random variables.
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