UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA

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+