Stein-type shrinkage techniques are applied to the parametric components of a semi-nonparametric regression model recently proposed by (Ma et al. 2015: 285–303). On the basis of an uncertain prior information (restrictions) about the parameters of interest, shrinkage techniques are shown to improve the accuracy of the model. The effectiveness of the proposed estimators are corroborated by a simulation study.

中文翻译：

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应用于半非参数回归模型的收缩估计

Stein 型收缩技术应用于最近由 (Ma et al. 2015: 285–303) 提出的半非参数回归模型的参数分量。在有关感兴趣参数的不确定先验信息（限制）的基础上，显示收缩技术可以提高模型的准确性。模拟研究证实了提议的估计器的有效性。