matlab/max_likelihood_cluster.m

   1 % To compute the model likelihood for a single observation, we add together\r
   2 % the probabilities of each of the underlying Markov Chains multiplied by\r
   3 % their priors.\r
   4 function likelihood = model_likelihood(observation, model)\r
   5 likelihood = 0;\r
   6 likelihood_vect = zeros(model.num_mcs, 1);\r
   7 for i=1:model.num_mcs\r
   8     likelihood_vect(i) = model.priors(i) * chain_likelihood(observation, model.chain(i));\r
   9 end\r
  10 likelihood_vect;\r
  11 likelihood = sum(likelihood_vect);\r
  12 \r
  13 % The likelihood of the observation for a single Markov Chain\r
  14 %function likelihood = chain_likelihood(observation, mc)\r
  15 %ikelihood = mc.t(observation(1));\r
  16 %for i=2:size(observation, 2)\r
  17 %    likelihood = likelihood * mc.T(observation(i-1), observation(i));\r
  18 %end