KNN Shannon Entropy Estimators.
entropy(X, k = 10, algorithm = c("kd_tree", "brute"))
an input data matrix.
the maximum number of nearest neighbors to search. The default value is set to 10.
nearest neighbor search algorithm.
a vector of length k
for entropy estimates using 1:k
nearest neighbors, respectively.
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.