Optimal method in multiple regression with structural changes
Optimal method in multiple regression with structural changes
复制标题
结构变化多元回归的最优方法
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
S. Nkurunziza
中科院分区：
文献类型：
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作者：
Fuqi Chen;S. Nkurunziza
本文研究了具有多个未知变点的多元回归模型中回归系数的估计问题。在一些现实的假设下，我们提出了一类估计，其中包括作为特殊情况收缩估计（SE）以及非限制估计（UE）和限制估计（RE）。我们还得到了一个更一般的条件SE主导UE。为此，我们推广了一些恒等式的估计的偏差和风险函数的收缩型估计。作为说明性的例子，我们的方法被应用到“国内生产总值”数据集的10个国家，其美国，加拿大，英国，法国和德国。仿真结果证实了我们的理论研究结果。
In this paper, we consider an estimation problem of the regression coefficients in multiple regression models with several unknown change-points. Under some realistic assumptions, we propose a class of estimators which includes as a special cases shrinkage estimators (SEs) as well as the unrestricted estimator (UE) and the restricted estimator (RE). We also derive a more general condition for the SEs to dominate the UE. To this end, we generalize some identities for the evaluation of the bias and risk functions of shrinkage-type estimators. As illustrative example, our method is applied to the "gross domestic product" data set of 10 countries whose USA, Canada, UK, France and Germany. The simulation results corroborate our theoretical findings.