Learn R Programming

FNN (version 1.1.4.1)

entropy: Shannon Entropy

Description

KNN Shannon Entropy Estimators.

Usage

entropy(X, k = 10, algorithm = c("kd_tree", "brute"))

Value

a vector of length k for entropy estimates using 1:k nearest neighbors, respectively.

Arguments

X

an input data matrix.

k

the maximum number of nearest neighbors to search. The default value is set to 10.

algorithm

nearest neighbor search algorithm.

Author

Shengqiao Li. To report any bugs or suggestions please email: lishengqiao@yahoo.com

References

H. Singh, N. Misra, V. Hnizdo, A. Fedorowicz and E. Demchuk (2003). “Nearest neighbor estimates of entropy”. American Journal of Mathematical and Management Sciences, 23, 301-321.

M.N. Goria, N.N.Leonenko, V.V. Mergel and P.L. Novi Inverardi (2005). “A new class of random vector entropy estimators and its applications in testing statistical hypotheses”. Journal of Nonparametric Statistics, 17:3, 277--297.

R.M. Mnatsakanov, N. Misra, S. Li and E.J. Harner (2008). “K_n-nearest neighbor estimators of entropy”. Mathematical Methods of Statistics, 17:3, 261-277.