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% Inference on a conditional Gaussian model
% Make the following polytree, where all arcs point down
% 1 2
% \ /
% 3
% / \
% 4 5
N = 5;
dag = zeros(N,N);
dag(1,3) = 1;
dag(2,3) = 1;
dag(3, [4 5]) = 1;
ns = [2 1 2 1 2];
dnodes = 1;
%onodes = [1 5];
bnet = mk_bnet(dag, ns, 'discrete', dnodes, 'observed', dnodes);
bnet.CPD{1} = tabular_CPD(bnet, 1);
for i=2:N
bnet.CPD{i} = gaussian_CPD(bnet, i);
end
engine = {};
engine{end+1} = jtree_inf_engine(bnet);
engine{end+1} = pearl_inf_engine(bnet, 'protocol', 'parallel');
[time, engine] = cmp_inference_static(bnet, engine, 'maximize', 0, 'check_ll', 0, ...
'singletons_only', 0, 'observed', [1 3]);
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