Change the default algorithm for stack_solve_algo = 0
The old algorithm (LBJ) is now available under stack_stock_algo = 6time-shift
Sébastien Villemot
parent
4b86df0581
commit
05dca0e3ea
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@ -2795,7 +2795,7 @@ Algorithm used for computing the solution. Possible values are:
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@item 0
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Newton method to solve simultaneously all the equations for every
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period, see @cite{Juillard (1996)} (Default).
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period, using sparse matrices (Default).
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@item 1
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Use a Newton algorithm with a sparse LU solver at each iteration
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@ -2821,6 +2821,13 @@ declaration}).
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Use a Newton algorithm with a sparse Gaussian elimination (SPE) solver
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at each iteration (requires @code{bytecode} option, @pxref{Model
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declaration}).
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@item 6
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Use the historical algorithm proposed in @cite{Juillard (1996)}: it is
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slower than @code{stack_solve_algo=0}, but may be less memory consuming
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on big models (not available with @code{bytecode} and/or @code{block}
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options).
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@end table
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@item markowitz = @var{DOUBLE}
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119
matlab/sim1.m
119
matlab/sim1.m
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@ -1,21 +1,19 @@
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function sim1
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% function sim1
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% performs deterministic simulations with lead or lag on one period
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% Performs deterministic simulations with lead or lag on one period.
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% Uses sparse matrices.
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%
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% INPUTS
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% ...
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% OUTPUTS
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% ...
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% ALGORITHM
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% Laffargue, Boucekkine, Juillard (LBJ)
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% see Juillard (1996) Dynare: A program for the resolution and
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% simulation of dynamic models with forward variables through the use
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% of a relaxation algorithm. CEPREMAP. Couverture Orange. 9602.
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% ...
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright (C) 1996-2010 Dynare Team
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% Copyright (C) 1996-2012 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -36,13 +34,19 @@ global M_ options_ oo_
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lead_lag_incidence = M_.lead_lag_incidence;
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ny = size(oo_.endo_simul,1) ;
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ny = M_.endo_nbr;
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max_lag = M_.maximum_endo_lag;
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nyp = nnz(lead_lag_incidence(1,:)) ;
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nyf = nnz(lead_lag_incidence(3,:)) ;
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nrs = ny+nyp+nyf+1 ;
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nrc = nyf+1 ;
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iyf = find(lead_lag_incidence(3,:)>0) ;
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iyp = find(lead_lag_incidence(1,:)>0) ;
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ny0 = nnz(lead_lag_incidence(2,:)) ;
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iy0 = find(lead_lag_incidence(2,:)>0) ;
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nyf = nnz(lead_lag_incidence(3,:)) ;
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iyf = find(lead_lag_incidence(3,:)>0) ;
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nd = nyp+ny0+nyf;
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nrc = nyf+1 ;
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isp = [1:nyp] ;
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is = [nyp+1:ny+nyp] ;
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isf = iyf+nyp ;
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@ -50,57 +54,63 @@ isf1 = [nyp+ny+1:nyf+nyp+ny+1] ;
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stop = 0 ;
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iz = [1:ny+nyp+nyf];
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periods = options_.periods
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steady_state = oo_.steady_state;
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params = M_.params;
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endo_simul = oo_.endo_simul;
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exo_simul = oo_.exo_simul;
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i_cols_1 = nonzeros(lead_lag_incidence(2:3,:)');
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i_cols_A1 = find(lead_lag_incidence(2:3,:)');
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i_cols_T = nonzeros(lead_lag_incidence(1:2,:)');
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i_cols_j = 1:nd;
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i_upd = ny+(1:periods*ny);
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Y = endo_simul(:);
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disp (['-----------------------------------------------------']) ;
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disp (['MODEL SIMULATION :']) ;
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fprintf('\n') ;
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it_init = M_.maximum_lag+1 ;
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model_dynamic = str2func([M_.fname,'_dynamic']);
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z = Y(find(lead_lag_incidence'));
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[d1,jacobian] = model_dynamic(z,oo_.exo_simul, params, ...
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steady_state,2);
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A = sparse([],[],[],periods*ny,periods*ny,periods*nnz(jacobian));
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res = zeros(periods*ny,1);
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h1 = clock ;
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for iter = 1:options_.maxit_
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h2 = clock ;
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if options_.terminal_condition == 0
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c = zeros(ny*options_.periods,nrc) ;
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else
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c = zeros(ny*(options_.periods+1),nrc) ;
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end
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i_rows = 1:ny;
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i_cols = find(lead_lag_incidence');
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i_cols_A = i_cols;
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it_ = it_init ;
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z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
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[d1,jacobian] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, M_.params, oo_.steady_state,it_);
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jacobian = [jacobian(:,iz) -d1] ;
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ic = [1:ny] ;
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icp = iyp ;
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c (ic,:) = jacobian(:,is)\jacobian(:,isf1) ;
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for it_ = it_init+(1:options_.periods-1)
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z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
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[d1,jacobian] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, ...
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M_.params, oo_.steady_state, it_);
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jacobian = [jacobian(:,iz) -d1] ;
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jacobian(:,[isf nrs]) = jacobian(:,[isf nrs])-jacobian(:,isp)*c(icp,:) ;
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ic = ic + ny ;
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icp = icp + ny ;
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c (ic,:) = jacobian(:,is)\jacobian(:,isf1) ;
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for it = 2:(periods+1)
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[d1,jacobian] = model_dynamic(Y(i_cols),exo_simul, params, ...
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steady_state,it);
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if it == 2
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A(i_rows,i_cols_A1) = jacobian(:,i_cols_1);
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elseif it == periods+1
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A(i_rows,i_cols_A(i_cols_T)) = jacobian(:,i_cols_T);
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else
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A(i_rows,i_cols_A) = jacobian(:,i_cols_j);
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end
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res(i_rows) = d1;
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i_rows = i_rows + ny;
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i_cols = i_cols + ny;
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if it > 2
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i_cols_A = i_cols_A + ny;
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end
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end
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if options_.terminal_condition == 1
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s = eye(ny) ;
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s(:,isf) = s(:,isf)+c(ic,1:nyf) ;
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ic = ic + ny ;
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c(ic,nrc) = s\c(ic,nrc) ;
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c = bksup1(c,ny,nrc,iyf,options_.periods) ;
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c = reshape(c,ny,options_.periods+1) ;
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oo_.endo_simul(:,it_init+(0:options_.periods)) = oo_.endo_simul(:,it_init+(0:options_.periods))+options_.slowc*c ;
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else
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c = bksup1(c,ny,nrc,iyf,options_.periods) ;
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c = reshape(c,ny,options_.periods) ;
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oo_.endo_simul(:,it_init+(0:options_.periods-1)) = oo_.endo_simul(:,it_init+(0:options_.periods-1))+options_.slowc*c ;
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end
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err = max(max(abs(c./options_.scalv')));
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disp([num2str(iter) ' - err = ' num2str(err)]) ;
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disp([' Time of iteration :' num2str(etime(clock,h2))]) ;
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err = max(abs(res));
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if err < options_.dynatol.f
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stop = 1 ;
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@ -112,10 +122,17 @@ for iter = 1:options_.maxit_
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oo_.deterministic_simulation.status = 1;% Convergency obtained.
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oo_.deterministic_simulation.error = err;
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oo_.deterministic_simulation.iterations = iter;
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oo_.endo_simul = reshape(Y,ny,periods+2);
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break
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end
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dy = -A\res;
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Y(i_upd) = Y(i_upd) + dy;
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end
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if ~stop
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fprintf('\n') ;
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disp([' Total time of simulation :' num2str(etime(clock,h1))]) ;
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@ -1,19 +1,22 @@
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function sim1a
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% function sim1a
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% Performs deterministic simulations with lead or lag on one period
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% Alternative algorithm to the one implemented in sim1
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function sim1_lbj
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% function sim1_lbj
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% performs deterministic simulations with lead or lag on one period
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% using the historical LBJ algorithm
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%
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% INPUTS
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% ...
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% OUTPUTS
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% ...
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% ALGORITHM
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% ...
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% Laffargue, Boucekkine, Juillard (LBJ)
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% see Juillard (1996) Dynare: A program for the resolution and
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% simulation of dynamic models with forward variables through the use
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% of a relaxation algorithm. CEPREMAP. Couverture Orange. 9602.
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright (C) 1996-2012 Dynare Team
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% Copyright (C) 1996-2010 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -34,19 +37,13 @@ global M_ options_ oo_
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lead_lag_incidence = M_.lead_lag_incidence;
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ny = M_.endo_nbr;
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max_lag = M_.maximum_endo_lag;
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ny = size(oo_.endo_simul,1) ;
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nyp = nnz(lead_lag_incidence(1,:)) ;
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iyp = find(lead_lag_incidence(1,:)>0) ;
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ny0 = nnz(lead_lag_incidence(2,:)) ;
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iy0 = find(lead_lag_incidence(2,:)>0) ;
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nyf = nnz(lead_lag_incidence(3,:)) ;
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iyf = find(lead_lag_incidence(3,:)>0) ;
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nd = nyp+ny0+nyf;
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nrs = ny+nyp+nyf+1 ;
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nrc = nyf+1 ;
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iyf = find(lead_lag_incidence(3,:)>0) ;
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iyp = find(lead_lag_incidence(1,:)>0) ;
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isp = [1:nyp] ;
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is = [nyp+1:ny+nyp] ;
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isf = iyf+nyp ;
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@ -54,63 +51,57 @@ isf1 = [nyp+ny+1:nyf+nyp+ny+1] ;
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stop = 0 ;
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iz = [1:ny+nyp+nyf];
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periods = options_.periods
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steady_state = oo_.steady_state;
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params = M_.params;
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endo_simul = oo_.endo_simul;
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exo_simul = oo_.exo_simul;
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i_cols_1 = nonzeros(lead_lag_incidence(2:3,:)');
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i_cols_A1 = find(lead_lag_incidence(2:3,:)');
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i_cols_T = nonzeros(lead_lag_incidence(1:2,:)');
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i_cols_j = 1:nd;
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i_upd = ny+(1:periods*ny);
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Y = endo_simul(:);
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disp (['-----------------------------------------------------']) ;
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disp (['MODEL SIMULATION :']) ;
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fprintf('\n') ;
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it_init = M_.maximum_lag+1 ;
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model_dynamic = str2func([M_.fname,'_dynamic']);
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z = Y(find(lead_lag_incidence'));
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[d1,jacobian] = model_dynamic(z,oo_.exo_simul, params, ...
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steady_state,2);
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A = sparse([],[],[],periods*ny,periods*ny,periods*nnz(jacobian));
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res = zeros(periods*ny,1);
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h1 = clock ;
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for iter = 1:options_.maxit_
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h2 = clock ;
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i_rows = 1:ny;
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i_cols = find(lead_lag_incidence');
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i_cols_A = i_cols;
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for it = 2:(periods+1)
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[d1,jacobian] = model_dynamic(Y(i_cols),exo_simul, params, ...
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steady_state,it);
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if it == 2
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A(i_rows,i_cols_A1) = jacobian(:,i_cols_1);
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elseif it == periods+1
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A(i_rows,i_cols_A(i_cols_T)) = jacobian(:,i_cols_T);
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else
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A(i_rows,i_cols_A) = jacobian(:,i_cols_j);
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end
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res(i_rows) = d1;
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i_rows = i_rows + ny;
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i_cols = i_cols + ny;
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if it > 2
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i_cols_A = i_cols_A + ny;
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end
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if options_.terminal_condition == 0
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c = zeros(ny*options_.periods,nrc) ;
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else
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c = zeros(ny*(options_.periods+1),nrc) ;
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end
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err = max(abs(res));
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it_ = it_init ;
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z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
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[d1,jacobian] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, M_.params, oo_.steady_state,it_);
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jacobian = [jacobian(:,iz) -d1] ;
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ic = [1:ny] ;
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icp = iyp ;
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c (ic,:) = jacobian(:,is)\jacobian(:,isf1) ;
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for it_ = it_init+(1:options_.periods-1)
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z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
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[d1,jacobian] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, ...
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M_.params, oo_.steady_state, it_);
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jacobian = [jacobian(:,iz) -d1] ;
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jacobian(:,[isf nrs]) = jacobian(:,[isf nrs])-jacobian(:,isp)*c(icp,:) ;
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ic = ic + ny ;
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icp = icp + ny ;
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c (ic,:) = jacobian(:,is)\jacobian(:,isf1) ;
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end
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if options_.terminal_condition == 1
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s = eye(ny) ;
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s(:,isf) = s(:,isf)+c(ic,1:nyf) ;
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ic = ic + ny ;
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c(ic,nrc) = s\c(ic,nrc) ;
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c = bksup1(c,ny,nrc,iyf,options_.periods) ;
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c = reshape(c,ny,options_.periods+1) ;
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oo_.endo_simul(:,it_init+(0:options_.periods)) = oo_.endo_simul(:,it_init+(0:options_.periods))+options_.slowc*c ;
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else
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c = bksup1(c,ny,nrc,iyf,options_.periods) ;
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c = reshape(c,ny,options_.periods) ;
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oo_.endo_simul(:,it_init+(0:options_.periods-1)) = oo_.endo_simul(:,it_init+(0:options_.periods-1))+options_.slowc*c ;
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end
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err = max(max(abs(c./options_.scalv')));
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disp([num2str(iter) ' - err = ' num2str(err)]) ;
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disp([' Time of iteration :' num2str(etime(clock,h2))]) ;
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if err < options_.dynatol.f
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stop = 1 ;
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@ -122,17 +113,10 @@ for iter = 1:options_.maxit_
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oo_.deterministic_simulation.status = 1;% Convergency obtained.
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oo_.deterministic_simulation.error = err;
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oo_.deterministic_simulation.iterations = iter;
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oo_.endo_simul = reshape(Y,ny,periods+2);
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break
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end
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dy = -A\res;
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Y(i_upd) = Y(i_upd) + dy;
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end
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if ~stop
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fprintf('\n') ;
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disp([' Total time of simulation :' num2str(etime(clock,h1))]) ;
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@ -33,18 +33,23 @@ global M_ options_ oo_
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test_for_deep_parameters_calibration(M_);
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if options_.stack_solve_algo < 0 || options_.stack_solve_algo > 5
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error('SIMUL: stack_solve_algo must be between 0 and 5')
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if options_.stack_solve_algo < 0 || options_.stack_solve_algo > 6
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error('SIMUL: stack_solve_algo must be between 0 and 6')
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end
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if ~options_.block && ~options_.bytecode && options_.stack_solve_algo ~= 0
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error('SIMUL: you must use stack_solve_algo=0 when not using block nor bytecode option')
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if ~options_.block && ~options_.bytecode && options_.stack_solve_algo ~= 0 ...
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&& options_.stack_solve_algo ~= 6
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error('SIMUL: you must use stack_solve_algo=0 or stack_solve_algo=6 when not using block nor bytecode option')
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end
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if options_.block && ~options_.bytecode && options_.stack_solve_algo == 5
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error('SIMUL: you can''t use stack_solve_algo = 5 without bytecode option')
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end
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if (options_.block || options_.bytecode) && options_.stack_solve_algo == 6
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error('SIMUL: you can''t use stack_solve_algo = 6 with block or bytecode option')
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end
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if exist('OCTAVE_VERSION') && options_.stack_solve_algo == 2
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error('SIMUL: you can''t use stack_solve_algo = 2 under Octave')
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end
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@ -91,7 +96,11 @@ else
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elseif M_.maximum_endo_lag == 0 % Purely forward model
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sim1_purely_forward;
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else % General case
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sim1;
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if options_.stack_solve_algo == 0
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sim1;
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else % stack_solve_algo = 6
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||||
sim1_lbj;
|
||||
end
|
||||
end
|
||||
end;
|
||||
end;
|
||||
|
|
|
|||
|
|
@ -78,7 +78,7 @@ for blockFlag = 0:1
|
|||
default_stack_solve_algo = 0;
|
||||
if ~blockFlag && ~bytecodeFlag
|
||||
solve_algos = 1:4;
|
||||
stack_solve_algos = 0;
|
||||
stack_solve_algos = [0 6];
|
||||
elseif blockFlag && ~bytecodeFlag
|
||||
solve_algos = [1:4 6:8];
|
||||
stack_solve_algos = 0:4;
|
||||
|
|
|
|||
|
|
@ -75,7 +75,7 @@ for blockFlag = 0:1
|
|||
default_stack_solve_algo = 0;
|
||||
if !blockFlag && !bytecodeFlag
|
||||
solve_algos = 0:4;
|
||||
stack_solve_algos = 0;
|
||||
stack_solve_algos = [0 6];
|
||||
elseif blockFlag && !bytecodeFlag
|
||||
solve_algos = [0:4 6 8];
|
||||
stack_solve_algos = [0 1 3 4];
|
||||
|
|
|
|||
Loading…
Reference in New Issue