Nearest neighbor estimates of Kaniadakis entropy

The aim of this paper is to develop new nonparametric estimators of entropy based on the k^th nearest neighbor distances that are considered between n sample points, k ≤ (n − 1) being a positive integer, fixed. The Method consists in using the new estimators which were useful in order to evaluate the entropies for random vectors. As results, using the Kaniadakis entropy measure, the asymptotic unbiasedness and consistency of the estimators are proven.