The function computes the k nearest neighbour sample entropy.
The sample from which to compute the entropy.
The order (number of neighbours) of the sample entropy calculation.
The sample entropy gives a measure of information in a (posterior) sample, or lack of it.
The k nearest neighbour entropy from the sample.
For high-dimensional posterior samples, the
nn.ent calculation is quite computationally intensive.
Nunes, M. A. and Prangle, D. (2016) abctools: an R package for tuning
approximate Bayesian computation analyses. The R Journal
7, Issue 2, 189–205.
Singh, H. et al. (2003) Nearest neighbor estimates of entropy. Am. J. Math. Man. Sci.,23, 301–321.
Shannon, C. E. and Weaver, W. (1948) A mathematical theory of communication. Bell Syst. Tech. J., 27, 379–423.
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