function [ la,le,ci ] = langendijk2002likelihood( p,rang,tang,target,response )
%LANGENDIJK2002LIKELIHOOD Likelihood estimation for evaluating model performance
% Usage: [la,le,ci] = langendijk2002likelihood(p,rang,tang,target,response)
%
% Input parameters:
% p : pdf matrix
% rang : polar angles of possible response angles
% tang : polar angles of possible target angles
% target : target polar angles of localization test
% response : response polar angles of localization test
%
% Output parameters:
% la : actual likelihood
% le : expected likelihood
% ci : 99% confidence interval for expected likelihood
%
% XXX Describe the function.
%
% See also: plot_langendijk2002likelihood, langendijk2002
%
% References:
% E. Langendijk and A. Bronkhorst. Contribution of spectral cues to human
% sound localization. J. Acoust. Soc. Am., 112:1583-1596, 2002.
%
%
%
% Url: http://amtoolbox.sourceforge.net/amt-0.9.7/doc/monaural/langendijk2002likelihood.php
% Copyright (C) 2009-2014 Peter L. Søndergaard and Piotr Majdak.
% This file is part of AMToolbox version 0.9.7
%
% This program 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 program 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 this program. If not, see <http://www.gnu.org/licenses/>.
% AUTHOR : Robert Baumgartner
nt=length(target);
% pa represents pdf values of actual responses
pa=interp2([-90;rang(:);270],[-90;tang(:);270], ...
[zeros(1,size(p,2)+2);[zeros(size(p,1),1),p,zeros(size(p,1),1)];...
zeros(1,size(p,2)+2)] ,target,response);
la=-2*sum(log(pa))*55/nt; % actual likelihood
% random generator
lex=zeros(100,1);
for ind=1:100
pe=zeros(size(target));
for ind1=1:nt
post=find(tang>=target(ind1),1); % target position
% post=randi(size(p,2),1);
posr = discreteinvrnd(p(:,post),1,1);
pe(ind1)=p(posr,post);
end
lex(ind)=-2*sum(log(pe))*55/nt;
end
le=mean(lex); % expected likelihood
err=2.58*std(lex);
ci=[le-err le+err]; % confidence interval
function [ X ] = discreteinvrnd(p,m,n)
% DISCRETEINVRND implements an inversion method for a discrete distribution
% with probability mass vector p and dimensions m,n
% Usage: [ X ] = discreteinvrnd(p,m,n)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% AUTHOR : Robert Baumgartner, OEAW
% latest update: 2010-07-21
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
X = zeros(m,n);
for i = 1:m*n
c = cumsum(p);
u = max(c)*rand;
X(i) = find(u < c ,1);
end