mixBernRnd, mixBernEm, nbBern not done

TODO.txt

@@ -1,5 +1,5 @@
 TODO: 
 extract demos
-ch08: BP, EP, NBMn
+ch08: BP, EP
 ch14: Cart
 

chapter09/Untitled.m

@@ -0,0 +1,17 @@
+close all; clear;
+d = 2;
+k = 3;
+n = 1000000;
+[X,z,mu] = mixBernRnd(d,k,n);
+model = nbBern(X,z);
+mu
+model.mu
+% [label,model,llh] = mixBernEm(X,k);
+% plot(llh);
+% d = 2;
+% n = 1000;
+% mu = rand(d,1);
+% X = bsxfun(@le,rand(d,n), mu);
+% 
+% m = mean(X,2)
+% mu

chapter09/mixBernRnd.m

@@ -7,16 +7,15 @@
 % Output:
 %   X: d x n data matrix
 %   z: 1 x n response variable
-%   center: d x k centers of clusters
+%   mu: d x k parameters of each Bernoulli component
 % Written by Mo Chen ([email protected]).
-alpha = 1;
 
-w = dirichletRnd(alpha,ones(1,k)/k);
+% w = dirichletRnd(1,ones(1,k)/k);
+w = ones(1,k)/k;
 z = discreteRnd(w,n);
-mu = rand(1,k);
-
+mu = rand(d,k);
 X = zeros(d,n);
 for i = 1:k
     idx = z==i;
-    X(:,idx) = rand(d,sum(idx)) < mu(k);
+    X(:,idx) = bsxfun(@le,rand(d,sum(idx)), mu(:,k));
 end