UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA
给出了密度函数和回归函数核估计量的一致收敛速度，适用于无限支撑的平稳强混合多元数据、无界支撑核和一般带宽序列，对基于第一阶段非参数估计的半参数估计有用。
This paper presents a set of rate of uniform consistency results for kernel estimators of density functions and regressions functions. We generalize the existing literature by allowing for stationary strong mixing multivariate data with infinite support, kernels with unbounded support, and general bandwidth sequences. These results are useful for semiparametric estimation based on a first-stage nonparametric estimator.