Optimal Bandwidth Selection in Nonparametric Regression Function Estimation

摘要

Kernel estimators of an unknown multivariate regression function are investigated. A bandwidth selection rule is considered, which can he formulated in terms of cross validation. Under mild assumptions on the kernel and the unknown regression function, it is seen that this rule is asymptotically optimal.