title: Choice of kernel function for density estimation.
abstract: Let l=f^n(x) be the kernel estimate of a density f(x) from a sample of size n. Wahba [6] has developed an upper bound to E[f(x)-l=f^n(x)]2. In the present paper, we find the kernel function of finite support [m=-T, T] that minimizes Wahba's upper bound. It is Q(y) = (1 + am=-1) (2T)m=-1 [1-m=-a|y|a] where a = 2-pm=-1, p m=ge 1.
authors.affiliation: Department of Electrical Engineering, State University of New York at Buffalo, Amherst, NY 14260.
authors.forename: D
authors.initials: D
authors.lastname: Kazakos