File size: 4,225 Bytes
d4035c1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
function [fv,p,mx,Cx,Cy,b]=CWM(y,x,Nc,iter,optim,Sigmax)
% Fit mixture of linear regressors


Dy=size(y,1); % Dimension de y
Nf=size(x,1); % Dimension de x
Nt=size(x,2); % Cantidad de datos

f1=figure;

Lk=0;

Lopt=10^100;
for opt=1:optim
    p=ones(Nc,1)/Nc; % p(Ci)

    gx=zeros(Nt,1);
    h=zeros(Nt,Nc);
    b=zeros(Dy,Nf+1,Nc);

    sigmay=cov(y');
    sigmax=cov(x');
    max(sigmax(:))

    MAXy=max(y(1,:)); MINy=min(y(1,:));


    mc=linspace(MINy,MAXy,Nc); 
    b(1,1,:)=mc+0*(rand(size(mc))-.5)*(MAXy-MINy)/Nc/2;
    %for i=1:Nc
    %    [m,n]=min(abs(y(1,:)-mc(i)));
    %end
    k=fix(rand(1,Nc)*Nt)+1;
    %cx=mean(x,2);
    for i=1:Nc
        mx(:,i)=x(:,k(i));
        b(:,1,i)=y(:,k(i));
        Cx(:,:,i)=.5*diag(diag(sigmax))/Nc^(1/Nf)+.5*eye(Nf,Nf)*max(sigmax(:))/Nc;
        Cy(:,:,i)=1*sigmay/Nc;
    end

    % E STEP:
    ss=0;

    %%%%%% Calulo de P(Cj|y,x)  -> h
    for j=1:Nc
        % Calculo de P(x,y|Cj)=P(y|x,Cj)*P(x|Cj)
        % P(x|Cj):
        xmx=x-repmat(mx(:,j),1,Nt);
        iXa=inv(Cx(:,:,j));
        xmX=iXa'*xmx;
        dxm=sum(xmX.*xmx)';
        % P(y|x,Cj):
        ym=y-b(:,:,j)*[ones(1,Nt); xmx];
        if Dy>1
            iXa=inv(Cy(:,:,j));
            ymY=ym'*iXa;
            dym=dot(ymY',ym)';
        else
            dym=ym'.^2/Cy(:,:,j);
        end

        gxy=exp(-0.5*(dym+dxm))/sqrt(det(Cy(:,:,j)))/(2*pi)^(Dy/2)/sqrt(det(Cx(:,:,j)))/(2*pi)^(Nf/2);
        gx(:,j)=exp(-0.5*(dxm))/sqrt(det(Cx(:,:,j)))/(2*pi)^(Nf/2);
        % P(y,x):
        h(:,j)=real(p(j)*gxy);
        ss=ss+h(:,j);
    end

    % E-M algorithm
    for k=1:iter        
        % visualization
        disp(k)
        figure(f1)
        subplot(121)
        cla
        plot(x(1,:),x(2,:),'y.')
        hold on
        plot(mx(1,:),mx(2,:),'+')
        axis('square')
        axis([min(x(1,:)) max(x(1,:)) min(x(2,:)) max(x(2,:))])
        drawnow
        subplot(122)
        cla
        hold on
        my=b(:,1,:);
        plot(my(1,:),mx(1,:),'+')
        axis('square')
        title('output')
        axis([min(y(1,:)) max(y(1,:)) min(x(1,:)) max(x(1,:))])
        drawnow

        for j=1:Nc
            h(:,j)=h(:,j)./ss;
        end
        tic

        % E
        ss=0;
        SUMtot=sum(h(:));
        shj=sum(h);
        Cxm=0;
        for j=1:Nc
            sh=shj(j);
            p(j)=sh/SUMtot;
            Cxm=Cxm+Cx(:,:,j)*p(j);
        end
        for j=1:Nc
            % M-STEP
            sh=shj(j);
            p(j)=sh/SUMtot;

            hDy=repmat(h(:,j)',Dy,1);
            hNf=repmat(h(:,j)',Nf,1);
            mx(:,j)=sum(hNf.*x,2)/sh;

            my=sum(hDy.*y,2)/sh;
            xmx=x-repmat(mx(:,j),1,Nt);
            xmxp=xmx';
            X=(hNf.*xmx)*xmxp/sh;
            Cx(:,:,j)=X+Sigmax*eye(Nf,Nf)/Nc^(1/Nf)*mean(diag(sigmax));
            iXa=pinv(Cx(:,:,j));

            % Calculo de b
            Bm=zeros(Nf+1,Nf+1); Bm(1,1)=1;
            Bm(2:Nf+1,2:Nf+1)=iXa;
            yxm=(hDy.*y)*xmxp/sh;
            Am=[my yxm];
            b(:,:,j)=Am*Bm';

            %calculo de Cy
            ym=y-b(:,:,j)*[ones(1,Nt); xmx];

            if Dy>1
                Cy(:,:,j)=(hDy.*ym)*ym'/sh+0.4*diag([10000/1 100/6].^2);
            else
                Cy(:,:,j)=(hDy.*ym)*ym'/sh+.1;
            end

            % STAGE E:
            iXa=pinv(Cxm);
            xmX=iXa'*xmx;
            dxm=sum(xmX.*xmx);
            % P(y|x,Cj):
            if Dy>1
                iXa=inv(Cy(:,:,j));
                ymY=iXa'*ym;
                dym=dot(ymY,ym);
            else
                dym=ym.*ym/Cy(:,:,j);
            end
            
            %gxy=exp(-0.5*(dym+dxm))/sqrt(det(Cy(:,:,j)))/(2*pi)^(Dy/2+Nf/2)*sqrt(det(iXa))/(2*pi)^(Nf/2);
            %size(gxy)
            % gx(:,j)=exp(-0.5*(dxm'))*sqrt(det(iXa))/(2*pi)^(Nf/2);
            % P(y,x):
            h(:,j)=p(j)*(exp(-0.5*dym)/sqrt(det(Cy(:,:,j)))/(2*pi)^(Dy/2)).*exp(-0.5*(dxm))*sqrt(det(iXa))/(2*pi)^(Nf/2);
            ss=ss+h(:,j);
        end
        toc

        L=-sum(log(ss));
        Lk(k,opt)=L;
    end

    p_opt=p;
    mx_opt=mx;
    Cx_opt=Cx;
    Cy_opt=Cy;
    b_opt=b;
    Lopt=L;
end
p=p_opt;
mx=mx_opt;
Cx=Cx_opt;
Cy=Cy_opt;
b=b_opt;


fv=Lopt;

close