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cisc/dr/fit_both_dir_discrete.m
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function [fct_fw, p_val_fw, fct_bw, p_val_bw]=fit_both_dir_discrete(X,cycX,Y,cycY,level,doplots) | |
%-fits a discrete additive noise model in both directions X->Y and Y->X. | |
% | |
%-X and Y should both be of size (n,1), | |
% | |
%-cycX is 1 if X should be modelled as a cyclic variable | |
% and 0 if not | |
%-cycY is 1 if Y should be modelled as a cyclic variable | |
% and 0 if not | |
% | |
%-level denotes the significance level of the independent test after which | |
%the algorithm should stop looking for a solution | |
% | |
%-doplots=1 shows a plot of the function and the residuals for each | |
%iteration (at the end there will be plots in each case) | |
% | |
%-example: | |
%pars.p_X=[0.1 0.3 0.1 0.1 0.2 0.1 0.1];pars.X_values=[-3;-2;-1;0;1;3;4]; | |
%pars2.p_n=[0.2 0.5 0.3];pars2.n_values=[-1;0;1]; | |
%[X Y]=add_noise(500,@(x) round(0.5*x.^2),'custom',pars,'custom',pars2, 'fct'); | |
% | |
%[fct1 p_val1 fct2 p_val2]=fit_both_dir_discrete(X,0,Y,0,0.05,0); | |
% | |
% | |
% | |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
% | |
%-please cite | |
% Jonas Peters, Dominik Janzing, Bernhard Schoelkopf (2010): Identifying Cause and Effect on Discrete Data using Additive Noise Models, | |
% in Y.W. Teh and M. Titterington (Eds.), Proceedings of The Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010, | |
% JMLR: W&CP 9, pp 597-604, Chia Laguna, Sardinia, Italy, May 13-15, 2010, | |
% | |
%-if you have problems, send me an email: | |
%jonas.peters ---at--- tuebingen.mpg.de | |
% | |
%Copyright (C) 2010 Jonas Peters | |
% | |
% This file is part of discrete_anm. | |
% | |
% discrete_anm 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. | |
% | |
% discrete_anm 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 discrete_anm. If not, see <http://www.gnu.org/licenses/>. | |
X=cell2mat(X); | |
Y=cell2mat(Y); | |
X=double(X'); | |
Y=double(Y'); | |
if cycY==0 | |
[fct_fw p_val_fw]=fit_discrete(X,Y,level,doplots,0); | |
elseif cycY==1 | |
[fct_fw p_val_fw]=fit_discrete_cyclic(X,Y,level,doplots,0); | |
end | |
if cycX==0 | |
[fct_bw p_val_bw]=fit_discrete(Y,X,level,doplots,1); | |
elseif cycX==1 | |
[fct_bw p_val_bw]=fit_discrete_cyclic(Y,X,level,doplots,1); | |
end | |
if p_val_fw>level | |
fct_fw | |
end | |
if p_val_bw>level | |
fct_bw | |
end | |
%p_val_fw | |
if p_val_fw>level | |
display('ANM could be fitted in the direction X->Y using fct_fw.'); | |
end | |
%p_val_bw | |
if p_val_bw>level | |
display('ANM could be fitted in the direction Y->X using fct_bw.'); | |
end | |
if (p_val_bw>level)&(p_val_fw<level) | |
display('Only one ANM could be fit. The method infers Y->X.'); | |
end | |
if (p_val_bw<level)&(p_val_fw>level) | |
display('Only one ANM could be fit. The method infers X->Y.'); | |
end | |
if (p_val_bw<level)&(p_val_fw<level) | |
display('No ANM could be fit. The method does not know the causal direction.'); | |
end | |
if (p_val_bw>level)&(p_val_fw>level) | |
display('Both ANM could be fit. The method does not know the causal direction.'); | |
end | |
%are X and Y independent? | |
p_val_ind=chi_sq_quant(X,Y,length(unique(X)),length(unique(Y))); | |
if p_val_ind>level | |
display('But note that X and Y are considered to be independent anyway. (Thus no causal relation.)'); | |
end | |