Generalized additive partially linear models enjoy the simplicity of GLMs and the flexibility of GAMs because they combine both parametric and nonparametric components. Based on spline-backfitted kernel estimator, we propose empirical likelihood (EL)-based pointwise confidence intervals and simultaneous confidence bands (SCBs) for the nonparametric component functions to make statistical inference. Simulation study strongly supports the asymptotic theory and shows that EL-based SCBs are much easier for implementation and have better performance than Wald-type SCBs. We apply the proposed method to a university retention study and provide SCBs for the effect of the students information.

广义加法部分线性模型具有GLM的简单性和GAM的灵活性，因为它们将参数和非参数成分结合在一起。基于样条反拟合的核估计器，我们提出了基于经验似然（EL）的点状置信区间和非参数分量函数的同时置信带（SCB）以进行统计推断。仿真研究强烈支持渐近理论，并表明基于EL的SCB比Wald型SCB易于实施且性能更好。我们将提出的方法应用于大学保留研究，并为学生信息的影响提供SCB。