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误差为AR(1)过程的半函数型偏线性回归模型参数估计的强收敛性 被引量:2

Strong convergence of parametric estimation in semi-functional partial linear regression model with AR(1) error
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摘要 文章研究了基于半函数型偏线性回归模型Y=XTβ+m(T)+ε,(X,T)与误差ε相互独立,在一定假设条件下,当误差满足AR(1)过程时,建立了这种半函数型偏线性回归模型中未知参数β的估计量β^的强收敛性,推广了现有文献中的结果。 The paper studies the semi-functional partial linear regression model Y=X^Tβ+m(T)+ε, in which(X, T) is independent of the error ε. Under some assumptions, the strong consistency of the estimator fl of the unknown parameter β in the semi-functional partial linear regression model is built with AR(1) error in this paper, and it extends the results in the related literature.
出处 《合肥工业大学学报(自然科学版)》 CAS CSCD 北大核心 2010年第4期616-620,共5页 Journal of Hefei University of Technology:Natural Science
基金 合肥工业大学精品课程资助项目(YJC2008Y07)
关键词 半函数型偏线性回归模型 函数型随机变量 强收敛性 AR(1)过程 semi-functional partial linear regression model functional random variable strong convergence AR(1) process
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参考文献22

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共引文献52

同被引文献13

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