The uniform convergence of nearest neighbor regression function estimators and their application in optimization

A class of nonparametric regression function estimates generalizing the nearest neighbor estimate of Cover 12 is presented. Under various noise conditions, it is shown that the estimates are strongly uniformly consistent. The uniform convergence of the estimates can be exploited to design a simple random search algorithm for the global minimization of the regression function.