On Consistency in Nonparametric Estimation under Mixing Conditions

In this paper a method for obtaining a.s. consistency in nonparametric estimation is presented which only requires the handling of covariances. This method is applied to kernel density estimation and kernel and nearest neighbour regression estimation. It leads to conditions for a.s. consistency which relax known conditions and include long-range dependence.