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1 function smallpot = marginalize_pot(bigpot, keep, maximize, useC)
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2 % MARGINALIZE_POT Marginalize a mpot onto a smaller domain.
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3 % smallpot = marginalize_pot(bigpot, keep, maximize, useC)
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4 %
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5 % The maximize argument is ignored - maxing out a Gaussian is the same as summing it out,
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6 % since the mode and mean are equal.
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7 % The useC argument is ignored.
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8
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9
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10 node_sizes = sparse(1, max(bigpot.domain));
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11 node_sizes(bigpot.domain) = bigpot.sizes;
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12 sum_over = mysetdiff(bigpot.domain, keep);
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13
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14 [logp, mu, Sigma] = marginalize_gaussian(bigpot.logp, bigpot.mu, bigpot.Sigma, ...
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15 keep, sum_over, node_sizes);
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16 smallpot = mpot(keep, node_sizes(keep), logp, mu, Sigma);
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17
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18 %%%%%%
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19
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20 function [logpX, muX, SXX] = marginalize_gaussian(logp, mu, Sigma, X, Y, ns)
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21 % MARGINALIZE_GAUSSIAN Compute Pr(X) from Pr(X,Y) where X and Y are jointly Gaussian.
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22 % [logpX, muX, SXX] = marginalize_gaussian(logp, mu, Sigma, X, Y, ns)
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23 %
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24 % sizes(i) is the size of the i'th block in domain.
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25
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26 [muX, muY, SXX, SXY, SYX, SYY] = partition_matrix_vec(mu, Sigma, X, Y, ns);
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27 logpX = logp; % Lauritzen (1996) p161
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