NEAREST-NEIGHBOR ENTROPY ESTIMATORS WITH WEAK METRICS

被引：1
|
作者：
Timofeev, Evgeniy [1 ]
Kaltchenko, Alexei [2 ]
机构：
[1] Yaroslavl State Univ, Dept Comp Sci, Yaroslavl, Russia
[2] Wilfrid Laurier Univ, Dept Phys & Comp Sci, Waterloo, ON N2L 3C5, Canada
来源：
ADVANCES IN MATHEMATICS OF COMMUNICATIONS | 2014年 / 8卷 / 02期
关键词：
Entropy; stochastic process; stationary; estimation; nonparametric; nearest neighbor; bias; metric; CONVERGENCE; SEQUENCES;
D O I：
10.3934/amc.2014.8.119
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A problem of improving the accuracy of nonparametric entropy estimation for a stationary ergodic process is considered. New weak metrics are introduced and relations between metrics, measures, and entropy are discussed. A new nonparametric entropy estimator is constructed based on weak metrics and has a parameter with which the estimator is optimized to reduce its bias. It is shown that estimator's variance is upper-bounded by a nearly optimal Cramer-Rao lower bound.
引用
收藏
页码：119 / 127
页数：9
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