Uniform in Bandwidth Consistency of Kernel Regression Estimators at a Fixed Point

We consider pointwise consistency properties of kernel regression function type estimators where the bandwidth sequence in not necessarily deterministic. In some recent papers uniform convergence rates over compact sets have been derived for such estimators via empirical process theory. We now show that it is possible to get optimal results in the pointwise case as well. The main new tool for the present work is a general moment bound for empirical processes which may be of independent interest.