+function [I] = IGV_estimation(Y,ds,co)

+%Estimates the generalized variance (I).

+% Y: Y(:,t) is the t^th sample.

+% ds: subspace dimensions.

+% co: initialized mutual information estimator object.

+% Zoltan Szabo and Andras Lorincz. Real and Complex Independent Subspace Analysis by Generalized Variance. ICA Research Network International Workshop (ICARN), pages 85-88, 2006.

+%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/>.

+if one_dimensional_problem(ds) && length(ds)==2

+ fs = IGV_dependency_functions;

+ num_of_functions = length(fs);

+ num_of_samples = size(Y,2);

+ %query for the current working environment:

+ environment_Matlab = working_environment_Matlab;

+ for k = 1 : num_of_functions %pick the k^th function (fs{k})

+ if strcmp(co.dependency,'cov')

+ c = (fY(:,1)-mean(fY(:,1))).' * (fY(:,2)-mean(fY(:,2))) / (num_of_samples-1);

+ I = I + c.^2; %cov instead of corr

+ if environment_Matlab%Matlab

+ I = I + (corr(fY(:,1),fY(:,2))).^2; %corr instead of cov

+ I = I + (cor(fY(:,1),fY(:,2))).^2; %cor (and not 'corr') instead of cov

+ error('There must be 2 pieces of one-dimensional subspaces (coordinates) for this estimator.');