ITE / code / H_I_D / base_estimators / HTsallis_kNN_k_estimation.m

function [H] = HTsallis_kNN_k_estimation(Y,co)
%Estimates the Tsallis entropy (H) of Y (Y(:,t) is the t^th sample)
%using the kNN method (S={k}). Cost parameters are provided in the cost object co.
%We make use of the naming convention 'H<name>_estimation', to ease embedding new entropy estimation methods.
%   Nikolai Leonenko, Luc Pronzato, and Vippal Savani. A class of Renyi information estimators for multidimensional densities. Annals of Statistics, 36(5):2153–2182, 2008.
%Copyright (C) 2012 Zoltan Szabo ("", "szzoli (at) cs (dot) elte (dot) hu")
%This file is part of the ITE (Information Theoretical Estimators) Matlab/Octave toolbox.
%ITE is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by
%the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
%This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of
%MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
%You should have received a copy of the GNU General Public License along with ITE. If not, see <>.


I_alpha = estimate_Ialpha(Y,co);
H = (1-I_alpha) / (co.alpha-1);