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1 function obslik = mk_hmm_obs_lik_matrix(engine, evidence)
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2
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3 T = size(evidence,2);
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4 Q = length(engine.startprob);
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5 obslik = ones(Q, T);
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6 bnet = bnet_from_engine(engine);
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7 % P(o1,o2| Q1,Q2) = P(o1|Q1,Q2) * P(o2|Q1,Q2)
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8 onodes = bnet.observed;
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9 for i=1:length(onodes)
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10 data = cell2num(evidence(onodes(i),:));
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11 if bnet.auto_regressive(onodes(i))
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12 params = engine.obsprob{i};
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13 mu = params.big_mu;
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14 Sigma = params.big_Sigma,
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15 W = params.big_W;
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16 mu0 = params.big_mu0;
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17 Sigma0 = params.big_Sigma0;
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18 %obslik_i = mk_arhmm_obs_lik(data, mu, Sigma, W, mu0, Sigma0
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19 obslik_i = clg_prob(data(:,1:T-1), data(:,2:T), mu, Sigma, W);
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20 obslik_i = [mixgauss_prob(data(:,1), mu0, Sigma0) obslik_i];
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21 elseif myismember(onodes(i), bnet.dnodes)
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22 %obslik_i = eval_pdf_cond_multinomial(data, engine.obsprob{i}.big_CPT);
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23 obslik_i = multinomial_prob(data, engine.obsprob{i}.big_CPT);
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24 else
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25 %obslik_i = eval_pdf_cond_gauss(data, engine.obsprob{i}.big_mu, engine.obsprob{i}.big_Sigma);
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26 obslik_i = mixgauss_prob(data, engine.obsprob{i}.big_mu, engine.obsprob{i}.big_Sigma);
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27 end
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28 obslik = obslik .* obslik_i;
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29 end
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30
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