Nearest-neighbor Entropy Estimators with Weak Metrics
Evgeniy Timofeev, Alexei Kaltchenko
TL;DR
A new nearest-neighbor entropy estimators is constructed and has a parameter with which the estimator is optimized to reduce its bias, and it is shown that estimator's variance is upper-bounded by a nearly optimal Cramer-Rao lower bound.
Abstract
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. Based on weak metrics, a new nearest-neighbor entropy estimator is constructed 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.
