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Statistical Estimation of the Shannon Entropy 被引量:4

Statistical Estimation of the Shannon Entropy
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摘要 The behavior of the Kozachenko–Leonenko estimates for the(differential) Shannon entropy is studied when the number of i.i.d. vector-valued observations tends to infinity. The asymptotic unbiasedness and L^2-consistency of the estimates are established. The conditions employed involve the analogues of the Hardy–Littlewood maximal function. It is shown that the results are valid in particular for the entropy estimation of any nondegenerate Gaussian vector. The behavior of the Kozachenko–Leonenko estimates for the(differential) Shannon entropy is studied when the number of i.i.d. vector-valued observations tends to infinity. The asymptotic unbiasedness and L^2-consistency of the estimates are established. The conditions employed involve the analogues of the Hardy–Littlewood maximal function. It is shown that the results are valid in particular for the entropy estimation of any nondegenerate Gaussian vector.
出处 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2019年第1期17-46,共30页 数学学报(英文版)
基金 Supported by the Russian Science Foundation(Grant No.14-21-00162)
关键词 Shannon differential entropy Kozachenko-Leonenko estimates HARDY-LITTLEWOOD maxi-mal function ANALOGUES ASYMPTOTIC UNBIASEDNESS and L^2-consistency Gaussian VECTORS Shannon differential entropy Kozachenko–Leonenko estimates Hardy–Littlewood maximal function analogues asymptotic unbiasedness and L^2-consistency Gaussian vectors
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