Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
445223 | AEU - International Journal of Electronics and Communications | 2010 | 5 Pages |
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
Authors
A. Kaltchenko, N. Timofeeva,