Remove bad_cond_flag argument from solve1.
This flag was not grounded on any solid theoretical foundation. This commit actually makes solve_algo=2 to be exactly the same than solve_algo=4.time-shift
Sébastien Villemot
parent
0bcc628ba3
commit
3fe5a728c6
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@ -109,7 +109,7 @@ function [dr,info] = dyn_risky_steadystate_solver(ys0,M, ...
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x0 = ys0(pm.v_p);
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n = length(x0);
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[x, info] = solve1(@risky_residuals_ds,x0,1:n,1:n,0,1, options.gstep, ...
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[x, info] = solve1(@risky_residuals_ds,x0,1:n,1:n,0,options.gstep, ...
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options.solve_tolf,options.solve_tolx, ...
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options.steady.maxit,options.debug,pm,M,dr, ...
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options,oo);
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@ -124,7 +124,7 @@ function [dr,info] = dyn_risky_steadystate_solver(ys0,M, ...
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pm = model_structure(M,options);
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end
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[ys, info] = solve1(func,ys0,1:endo_nbr,1:endo_nbr,0,1, options.gstep, ...
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[ys, info] = solve1(func,ys0,1:endo_nbr,1:endo_nbr,0,options.gstep, ...
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options.solve_tolf,options.solve_tolx, ...
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options.steady.maxit,options.debug,pm,M,dr,options,oo);
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% [ys, info] = csolve(func,ys0,[],1e-10,100,M,dr,options,oo);
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@ -120,7 +120,7 @@ if options_.solve_algo == 0
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info = 1;
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end
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elseif options_.solve_algo == 1
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[x,info]=solve1(func,x,1:nn,1:nn,jacobian_flag,1,options_.gstep, ...
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[x,info]=solve1(func,x,1:nn,1:nn,jacobian_flag,options_.gstep, ...
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tolf,options_.solve_tolx, ...
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options_.steady.maxit,options_.debug,varargin{:});
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elseif options_.solve_algo == 2 || options_.solve_algo == 4
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@ -140,15 +140,12 @@ elseif options_.solve_algo == 2 || options_.solve_algo == 4
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disp(['DYNARE_SOLVE (solve_algo=2|4): number of blocks = ' num2str(length(r))]);
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end
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% Activate bad conditioning flag for solve_algo = 2, but not for solve_algo = 4
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bad_cond_flag = (options_.solve_algo == 2);
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for i=length(r)-1:-1:1
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if options_.debug
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disp(['DYNARE_SOLVE (solve_algo=2|4): solving block ' num2str(i) ', of size ' num2str(r(i+1)-r(i)) ]);
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end
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[x,info]=solve1(func,x,j1(r(i):r(i+1)-1),j2(r(i):r(i+1)-1),jacobian_flag, ...
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bad_cond_flag, options_.gstep, ...
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options_.gstep, ...
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tolf,options_.solve_tolx, ...
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options_.steady.maxit,options_.debug,varargin{:});
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if info
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@ -157,7 +154,7 @@ elseif options_.solve_algo == 2 || options_.solve_algo == 4
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end
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fvec = feval(func,x,varargin{:});
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if max(abs(fvec)) > tolf
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[x,info]=solve1(func,x,1:nn,1:nn,jacobian_flag, bad_cond_flag, ...
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[x,info]=solve1(func,x,1:nn,1:nn,jacobian_flag, ...
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options_.gstep, tolf,options_.solve_tolx, ...
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options_.steady.maxit,options_.debug,varargin{:});
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end
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@ -41,7 +41,7 @@ function sim1_purely_backward()
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yb1 = yb(iyb);
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tmp = solve1(model_dynamic, [yb1; yb], 1:M_.endo_nbr, nyb+1:nyb+ ...
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M_.endo_nbr, 1, 1, options_.gstep, ...
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M_.endo_nbr, 1, options_.gstep, ...
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options_.solve_tolf,options_.solve_tolx, ...
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options_.simul.maxit,options_.debug,oo_.exo_simul, ...
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M_.params, oo_.steady_state, it);
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@ -34,7 +34,7 @@ function sim1_purely_forward()
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yf1 = yf(iyf);
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tmp = solve1(model_dynamic, [yf; yf1], 1:M_.endo_nbr, 1:M_.endo_nbr, ...
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1, 1, options_.gstep, options_.solve_tolf, ...
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1, options_.gstep, options_.solve_tolf, ...
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options_.solve_tolx, options_.simul.maxit, ...
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options_.debug,oo_.exo_simul, M_.params, oo_.steady_state, ...
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it);
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@ -105,7 +105,7 @@ DynareOutput.endo_simul(:,1) = DynareOutput.steady_state;
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for it = 2:sample_size+1
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y(jdx) = DynareOutput.endo_simul(:,it-1); % A good guess for the initial conditions is the previous values for the endogenous variables.
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y(hdx) = y(jdx(iy1)); % Set lagged variables.
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y(jdx) = solve1(model_dynamic, y, idx, jdx, 1, 1, DynareOptions.gstep, ...
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y(jdx) = solve1(model_dynamic, y, idx, jdx, 1, DynareOptions.gstep, ...
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DynareOptions.solve_tolf,DynareOptions.solve_tolx, ...
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DynareOptions.simul.maxit,DynareOptions.debug, ...
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DynareOutput.exo_simul, DynareModel.params, ...
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@ -1,5 +1,4 @@
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function [x,check] = solve1(func,x,j1,j2,jacobian_flag,bad_cond_flag,gstep,tolf,tolx,maxit,debug,varargin)
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% function [x,check] = solve1(func,x,j1,j2,jacobian_flag,bad_cond_flag,varargin)
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function [x,check] = solve1(func,x,j1,j2,jacobian_flag,gstep,tolf,tolx,maxit,debug,varargin)
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% Solves systems of non linear equations of several variables
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%
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% INPUTS
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@ -9,15 +8,13 @@ function [x,check] = solve1(func,x,j1,j2,jacobian_flag,bad_cond_flag,gstep,tolf,
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% j2: unknown variables index
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% jacobian_flag=1: jacobian given by the 'func' function
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% jacobian_flag=0: jacobian obtained numerically
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% bad_cond_flag=1: when Jacobian is badly conditionned, use an
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% alternative formula to Newton step
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% gstep increment multiplier in numercial derivative
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% computation
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% tolf tolerance for residuals
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% tolx tolerance for solution variation
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% maxit maximum number of iterations
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% debug debug flag
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% varargin: list of arguments following bad_cond_flag
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% varargin: list of extra arguments to the function
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%
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% OUTPUTS
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% x: results
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@ -26,7 +23,7 @@ function [x,check] = solve1(func,x,j1,j2,jacobian_flag,bad_cond_flag,gstep,tolf,
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2001-2012 Dynare Team
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% Copyright (C) 2001-2014 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -95,7 +92,7 @@ for its = 1:maxit
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if debug
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disp(['cond(fjac) ' num2str(cond(fjac))])
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end
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if bad_cond_flag && rcond(fjac) < sqrt(eps)
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if rcond(fjac) < sqrt(eps)
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fjac2=fjac'*fjac;
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p=-(fjac2+1e6*sqrt(nn*eps)*max(sum(abs(fjac2)))*eye(nn))\(fjac'*fvec);
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else
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