40 lines
924 B
Mathematica
40 lines
924 B
Mathematica
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function sigma_sq = mstep_update_noisevar_md(P, S_bar, V, E_z, E_zz, RO, Tr)
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%sigma_sq = mstep_update_noisevar(P, S_bar, V, E_z, E_zz, RO, Tr)
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% Updates noise variance (Eq 22)
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[K, T] = size(E_z);
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J = size(S_bar, 2);
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M_t = zeros(2*J, K);
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sigma_sq = 0;
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for t = 1:T,
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R_t = RO{t};
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Sdef = S_bar;
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for kk = 1:K,
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Sdef = Sdef + E_z(kk,t)*V((kk-1)*3+[1:3],:);
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M_t(1:J, kk) = (R_t(1,:)*V((kk-1)*3+[1:3],:))';
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M_t(J+1:end, kk) = (R_t(2,:)*V((kk-1)*3+[1:3], :))';
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end;
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f_bar_t = R_t(1:2,:)*S_bar;
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f_bar_t = [f_bar_t(1,:) f_bar_t(2,:)]';
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f_t = [P(t, :) P(t+T, :)]';
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t_vect_t = [Tr(t,1)*ones(J,1); Tr(t,2)*ones(J,1)];
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s1 = (f_t - f_bar_t - t_vect_t)'*(f_t - f_bar_t - t_vect_t);
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s2 = 2*(f_t - f_bar_t - t_vect_t)'*M_t*E_z(:,t);
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s3 = trace(M_t'*M_t*E_zz((t-1)*K+1:t*K,:));
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sigma_sq = sigma_sq + (s1 - s2 + s3);
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end
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sigma_sq = sigma_sq/(2*J*T);
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