56 lines
1.4 KiB
Matlab
56 lines
1.4 KiB
Matlab
function J = EvalModelJacobian()
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% Evaluates the Jacobian matrix associated to a model.
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%
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% INPUTS
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% None.
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%
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% OUTPUTS
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% o J a matlab structure: J.Eq1.<VARIABLE_NAME>.[<lag_><lead_>h]or[current]
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%
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% ALGORITHM
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%
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%
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% SPECIAL REQUIREMENTS
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% None.
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%
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%
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% part of DYNARE, copyright S. Adjemian, M. Juillard (2006)
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% Gnu Public License.
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global options_ M_ oo_
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klen = M_.maximum_lag + M_.maximum_lead + 1;
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iyv = M_.lead_lag_incidence';
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% [(t-M_.maximum_lag);...;(t-1);t;(t+1);...;t+M_.maximum_lead] for each
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% column (variable) of M_.lead_lag_incidence.
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iyv = iyv(:);
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iyr0 = find(iyv) ;
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if M_.exo_nbr == 0
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oo_.exo_steady_state = [] ;
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end
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tx = oo_.exo_simul;
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dr = oo_.dr;
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z = repmat(dr.ys,1,klen);
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z = z(iyr0) ;
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[junk,jacobia_] = feval([M_.fname '_dynamic'],z,tx);
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for eq = 1:M_.endo_nbr
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for var = 1:M_.endo_nbr
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for h = -M_.maximum_lag:1:M_.maximum_lead
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linee = h+M_.maximum_lag+1;
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if h<0
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name = ['lag_' int2str(abs(h))];
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elseif h == 0
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name = ['current'];
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else
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name = ['lead_' int2str(h)];
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end
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if M_.lead_lag_incidence(linee,var) == 0
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eval(['J.Eq' int2str(eq) '.' deblank(M_.endo_names(var,:)) '.' name ' = 0;'])
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else
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idx = M_.lead_lag_incidence(linee,var);
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eval(['J.Eq' int2str(eq) '.' deblank(M_.endo_names(var,:)) '.' name ' = jacobia_(eq,idx);'])
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end
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end
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end
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end |