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Daniel Wolff |
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Fri, 19 Aug 2016 13:07:06 +0200 |
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1 function g = demgpot(x, mix)
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2 %DEMGPOT Computes the gradient of the negative log likelihood for a mixture model.
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3 %
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4 % Description
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5 % This function computes the gradient of the negative log of the
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6 % unconditional data density P(X) with respect to the coefficients of
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7 % the data vector X for a Gaussian mixture model. The data structure
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8 % MIX defines the mixture model, while the matrix X contains the data
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9 % vector as a row vector. Note the unusual order of the arguments: this
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10 % is so that the function can be used in DEMHMC1 directly for sampling
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11 % from the distribution P(X).
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12 %
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13 % See also
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14 % DEMHMC1, DEMMET1, DEMPOT
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15 %
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16
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17 % Copyright (c) Ian T Nabney (1996-2001)
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18
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19 % Computes the potential gradient
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20
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21 temp = (ones(mix.ncentres,1)*x)-mix.centres;
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22 temp = temp.*(gmmactiv(mix,x)'*ones(1, mix.nin));
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23 % Assume spherical covariance structure
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24 if ~strcmp(mix.covar_type, 'spherical')
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25 error('Spherical covariance only.')
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26 end
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27 temp = temp./(mix.covars'*ones(1, mix.nin));
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28 temp = temp.*(mix.priors'*ones(1, mix.nin));
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29 g = sum(temp, 1)/gmmprob(mix, x); |
