On the Strong Universal Consistency of Nearest Neighbor Regression Function Estimates

Abstract

Two results are presented concerning the consistency of the k-nearestneighbor regression estimate. We show that all modes of convergencein L1 (in probability, almost sure, complete) are equivalent if theregression variable is bounded. Under the additional conditionalk/log n ? ? we also obtain the strong universal consistency of theestimate.