Article ID Journal Published Year Pages File Type
445223 AEU - International Journal of Electronics and Communications 2010 5 Pages PDF
Abstract

The nearest neighbor entropy estimator was previously shown to converge for a broad class of stationary ergodic measures. In this paper, it is established that the estimator converges at a rate slower than O(1/logn)O(1/logn), where n is the number of observations. For the class of the symmetric Bernoulli measures an explicit formulae (see (7)) for the estimator's bias is obtained.1

Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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