THE EQUIVALENCE OF WEAK , STRONG AND COMPLETE CONVERGENCE IN Ll FOR KERNEL DENSITY ESTIMATES ' BY LUC DEVROYE McGill

Let f be a density on R", and let f, be the kernel estimate off, fn(x) _ (nh d)-' ~= 1 K((x-X1)lh) where h = h n is a sequence of positive numbers, and K is an absolutely integrable function with f K(x) dx =1. Let J, = f l f ,(x)-f (x) (dx. We show that when limn h = 0 and limnnh d = oo, then for every e > 0 there exist constants r, no > 0 such that P(Jn > e) <_ exp(-rn), n ? no. Also, when J,-p 0 in probability as n-p oo and K is a density, then limn h = 0 and limnnhd = oo.

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