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Nearest neighbor estimates of entropy.

Authors
Singh-H; Misra-N; Hnizdo-V; Fedorowicz-A; Demchuk-E
Source
Am J Math Manage Sci 2003 Jul; 23(3-4):301-321
NIOSHTIC No.
20025458
Abstract
Motivated by the problems in molecular sciences, we introduce new parametric estimates of entropy which are based on the kth nearest neighbor distances between the n sample points, where k (< n - 1) is a fixed positive integer. These provide competing esitmators to an estimator proposed by Kozachenko and Leonenko (1987), which is based on the first nearest neighbor distances of the sample points. These estimators are helpful in the evaluation of entropies of random vectors. We establish the asymptotic unbiasedness and consistency of the proposed estimators. For some standard distributions, we also investigate their performance for finite sample sizes using Monte Carlo simulations. The proposed estimators are applied to estimate the entropy of internal rotation in the methanol molecule, which can be characterized by a one-dimensional random vector, and of diethyl ether, which is described by a four-dimensional random vector.
Keywords
Sampling; Sampling-methods; Simulation-methods; Ethers; Statistical-analysis; Mathematical-models
CODEN
AMMSDX
CAS No.
60-29-7
Publication Date
20030701
Document Type
Journal Article
Fiscal Year
2003
NTIS Accession No.
NTIS Price
Issue of Publication
3-4
ISSN
0196-6324
NIOSH Division
HELD
Source Name
American Journal of Mathematical and Management Sciences
State
WV
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