“School of Biological”
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| Paper IPM / Biological / 15029 |
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| Abstract: | |||||
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This article is concerned with nonparametric estimation of the entropy
in ranked set sampling. Theoretical properties of the proposed estimator
are studied. The proposed estimator is compared with the rival estima-
tor in simple random sampling. The applications of the proposed esti-
mator to themutual information estimation as well as estimation of the
KullbackâLeibler divergence are provided. Several Monté-Carlo simula-
tion studies are conducted to examine the performance of the estima-
tor. The results are applied to the longleaf pine (Pinus palustris) trees and
the body fat percentage datasets to illustrate applicability of theoretical
results.
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