刘宣, 马海强. 函数型线性回归模型的变点检验[J]. 应用概率统计, 2023, 39(4): 475-490. DOI: 10.3969/j.issn.1001-4268.2023.04.001
引用本文: 刘宣, 马海强. 函数型线性回归模型的变点检验[J]. 应用概率统计, 2023, 39(4): 475-490. DOI: 10.3969/j.issn.1001-4268.2023.04.001
LIU Xuan, MA Haiqiang. Detecting Changes in the Functional Linear Regression Model[J]. Chinese Journal of Applied Probability and Statistics, 2023, 39(4): 475-490. DOI: 10.3969/j.issn.1001-4268.2023.04.001
Citation: LIU Xuan, MA Haiqiang. Detecting Changes in the Functional Linear Regression Model[J]. Chinese Journal of Applied Probability and Statistics, 2023, 39(4): 475-490. DOI: 10.3969/j.issn.1001-4268.2023.04.001

函数型线性回归模型的变点检验

Detecting Changes in the Functional Linear Regression Model

  • 摘要: 本文研究了解释变量为过程, 响应变量为标量的函数型线性回归模型的变点检验问题. 基于投影矩估计量, 在截断的有限维空间上, 论文给出了检验统计量和变点估计量, 获得了检验统计量的渐近分布, 并在一定的条件下证明了变点估计量的相合性. 数值模拟和实际数据分析呈现了所提方法的有限样本表现.

     

    Abstract: In this paper, we consider the change-point problems for the functional linear model, where the explanatory variable is a random process, and the response is a scalar. Based on the projecting moment estimators of the parameters onto the truncated finite-dimensional space, we propose the detecting statistic and give the estimator of the change-point. In a theoretical investigation, we derive the asymptotic distribution for the proposed detecting statistic, and establish the consistency of the change-point estimate under some mild conditions. Some simulation studies and a real data analysis are conducted to illustrate the finite performance of the proposed testing methods.

     

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