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Zoltan Szabo committed b5181ca

'Tsallis entropy <- Renyi entropy' meta estimator: added; see 'HTsallis_HRenyi_initialization.m', 'HTsallis_HRenyi_estimation.m'.

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+-'Tsallis entropy <- Renyi entropy' meta estimator: added; see 'HTsallis_HRenyi_initialization.m', 'HTsallis_HRenyi_estimation.m'. 
+
 v0.16 (Nov 2, 2012):
 -Edgeworth expansion based Shannon entropy estimator: added; see 'HShannon_Edgeworth_initialization.m', 'HShannon_Edgeworth_estimation.m'.
 -Lookup table for the underlying H/I/D estimation formulas: added (see ITE_documentation.pdf: Section C).
 -Hoeffding's Phi computation: scaled-up (C++); see 'Hoeffding_term1.cpp'.
 -HRenyi_weightedkNN_initialization.m: contained a superfluous co.k parameter, deleted.
 -chol_gauss.c: a superfluous 'double *y' variable deleted.
--dY==dX verification added to 'DRenyi_kNN_k_estimation.m', 'DTsallis_kNN_k_estimation.m', 'DL2_kNN_k_estimation.m'.
+-dY==dX (dimension of Y and X) verification added to 'DRenyi_kNN_k_estimation.m', 'DTsallis_kNN_k_estimation.m', 'DL2_kNN_k_estimation.m'.
 -some comments improved.
 
 v0.11 (Oct 20, 2012):

code/H_I_D/meta_estimators/HTsallis_HRenyi_estimation.m

+function [H] = HTsallis_HRenyi_estimation(Y,co)
+%Estimates the Tsallis entropy (H) of Y (Y(:,t) is the t^th sample)
+%using via the Renyi entropy and the H_{T,alpha} = (e^{H_{R,alpha}(1-alpha)} - 1) / (1-alpha) relation. 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.
+%
+%Copyright (C) 2012 Zoltan Szabo ("http://nipg.inf.elte.hu/szzoli", "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 <http://www.gnu.org/licenses/>.
+
+%co.mult:OK.
+
+H =  H_estimation(Y,co.member_co); %Renyi entropy
+H = (exp(H * (1-co.alpha)) - 1) / (1-co.alpha); %Renyi->Tsallis entropy
+

code/H_I_D/meta_estimators/HTsallis_HRenyi_initialization.m

+function [co] = HTsallis_HRenyi_initialization(mult)
+%Initialization of the meta Tsallis entropy estimator defined according to the relation: H_{T,alpha} = (e^{H_{R,alpha}(1-alpha)} - 1) / (1-alpha), where H_{T,alpha} and H_{R,alpha} denotes the Tsallis and the Renyi entropy, respectively.
+%
+%Note:
+%   1)The estimator is treated as a cost object (co).
+%   2)We make use of the naming convention 'H<name>_initialization', to ease embedding new entropy estimation methods.
+%
+%INPUT:
+%   mult: is a multiplicative constant relevant (needed) in the estimation; '=1' means yes, '=0' no.
+%OUTPUT:
+%   co: cost object (structure).
+%
+%Copyright (C) 2012 Zoltan Szabo ("http://nipg.inf.elte.hu/szzoli", "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 <http://www.gnu.org/licenses/>.
+
+%mandatory fields:
+    co.name = 'Tsallis_HRenyi';
+    co.mult = mult;
+    
+%other fields:
+    co.alpha = 0.95; 
+
+    co.member_name = 'Renyi_kNN_k'; %you can change it to any Renyi entropy estimator
+    co.member_co = H_initialization(co.member_name,mult);
+    co.member_co.alpha = co.alpha;

code/IPA/optimization/clustering_UD0.m

 %   cost_name: depending on entropy/mutual information based ISA formulation [see below A)-F)], it can take the values:
 %   i)entropy:
 %       a)base methods: 'Shannon_kNN_k', 'Renyi_kNN_k', 'Renyi_kNN_1tok', 'Renyi_kNN_S', 'Renyi_weightedkNN', 'Renyi_MST', 'Renyi_GSF', 'Tsallis_kNN_k', 'Shannon_Edgeworth'.
-%       b)meta methods: 'complex', 'ensemble', 'RPensemble'.
+%       b)meta methods: 'complex', 'ensemble', 'RPensemble', 'Tsallis_HRenyi'.
 %   ii)mutual information:
 %       a)base methods: 'GV', 'KCCA', 'KGV', 'HSIC', 'Hoeffding', 'SW1', 'SWinf'.
 %       b)meta methods: 
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doc/ITE_documentation.pdf

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