Rates of convergence of nearest neighbor estimation under arbitrary sampling

Abstract

Rates of convergence for nearest neighbor estimation are established in a general framework in terms of metric covering numbers of the underlying space. Our first result is to find explicit finite sample upper bounds for the classical independent and identically distributed (i.i.d.) random sampling problem in a separable metric space setting. The… (More)
DOI: 10.1109/18.391248

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