@inproceedings{069596daaed243fa89e20b44e9293b34,

title = "Estimation by the nearest neighbor rule under arbitrary sampling",

abstract = "We introduce a new estimation problem in which the samples can be chosen arbitrarily. We show that for every sequence of samples the asymptotic time-average of nearest neighbor risks equals twice the time-average of the conditional Bayes risks of the sequence. Rates of convergence for nearest neighbor estimation are established in terms of metric covering numbers of the underlying space. In particular, for compact subsets of Rr the convergence rate of the time-averaged risk is O(1/n2/r).",

author = "Posner, {S. E.} and Kulkarni, {S. R.}",

year = "1994",

month = dec,

day = "1",

doi = "10.1109/ISIT.1994.394930",

language = "English (US)",

isbn = "0780320158",

series = "IEEE International Symposium on Information Theory - Proceedings",

booktitle = "Proceedings - 1994 IEEE International Symposium on Information Theory, ISIT 1994",

note = "1994 IEEE International Symposium on Information Theory, ISIT 1994 ; Conference date: 27-06-1994 Through 01-07-1994",

}