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Nearest neighbor estimates of entropy for multivariate circular distributions.

Authors
Misra-N; Singh-H; Hnizdo-V
Source
Entropy 2010 May; 12(5):1125-1144
NIOSHTIC No.
20036961
Abstract
In molecular sciences, the estimation of entropies of molecules is important for the understanding of many chemical and biological processes. Motivated by these applications, we consider the problem of estimating the entropies of circular random vectors and introduce non-parametric estimators based on circular distances between n sample points and their k th nearest neighbors (NN), where k (<= n - 1) is a fixed positive integer. The proposed NN estimators are based on two different circular distances, and are proven to be asymptotically unbiased and consistent. The performance of one of the circular-distance estimators is investigated and compared with that of the already established Euclidean-distance NN estimator using Monte Carlo samples from an analytic distribution of six circular variables of an exactly known entropy and a large sample of seven internal-rotation angles in the molecule of tartaric acid, obtained by a realistic molecular-dynamics simulation.
Keywords
Analytical-methods; Chemical-composition; Chemical-structure; Mathematical-models; Molecular-biology; Molecular-structure; Standards; Statistical-analysis; Thermodynamic-reactions; Author Keywords: circular random variables; differential entropy; non-parametric estimation; nearest neighbor; circular distance; molecular simulation
CODEN
ENTRFG
Publication Date
20100501
Document Type
Journal Article
Email Address
neeraj@iitk.ac.in
Fiscal Year
2010
NTIS Accession No.
NTIS Price
Issue of Publication
5
ISSN
1099-4300
NIOSH Division
HELD
Source Name
Entropy
State
WV
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