steady: turn homotopy{1,2,3} into local functions
Sébastien Villemot
parent
def25a1fd3
commit
1a421d93dd
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@ -1,99 +0,0 @@
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function [M,oo,info,ip,ix,ixd] = homotopy1(values, step_nbr, M, options, oo)
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% function homotopy1(values, step_nbr)
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%
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% Implements homotopy (mode 1) for steady-state computation.
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% The multi-dimensional vector going from the set of initial values
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% to the set of final values is divided in as many sub-vectors as
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% there are steps, and the problem is solved as many times.
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%
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% INPUTS
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% values: a matrix with 4 columns, representing the content of
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% homotopy_setup block, with one variable per line.
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% Column 1 is variable type (1 for exogenous, 2 for
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% exogenous deterministic, 4 for parameters)
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% Column 2 is symbol integer identifier.
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% Column 3 is initial value, and column 4 is final value.
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% Column 3 can contain NaNs, in which case previous
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% initialization of variable will be used as initial value.
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% step_nbr: number of steps for homotopy
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% M struct of model parameters
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% options struct of options
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% oo struct of outputs
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%
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% OUTPUTS
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% M struct of model parameters
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% oo struct of outputs
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% ip index of parameters
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% ix index of exogenous variables
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% ixp index of exogenous deterministic variables
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright © 2008-2022 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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nv = size(values, 1);
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ip = find(values(:,1) == 4); % Parameters
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ix = find(values(:,1) == 1); % Exogenous
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ixd = find(values(:,1) == 2); % Exogenous deterministic
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if length([ip; ix; ixd]) ~= nv
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error('HOMOTOPY mode 1: incorrect variable types specified')
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end
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% Construct vector of starting values, using previously initialized values
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% when initial value has not been given in homotopy_setup block
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oldvalues = values(:,3);
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ipn = find(values(:,1) == 4 & isnan(oldvalues));
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oldvalues(ipn) = M.params(values(ipn, 2));
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ixn = find(values(:,1) == 1 & isnan(oldvalues));
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oldvalues(ixn) = oo.exo_steady_state(values(ixn, 2));
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ixdn = find(values(:,1) == 2 & isnan(oldvalues));
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oldvalues(ixdn) = oo.exo_det_steady_state(values(ixdn, 2));
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points = zeros(nv, step_nbr+1);
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for i = 1:nv
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if (oldvalues(i) ~= values(i, 4))
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points(i,:) = oldvalues(i):(values(i,4)-oldvalues(i))/step_nbr:values(i,4);
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else
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points(i,:) = values(i,4);
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end
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end
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for i=1:step_nbr+1
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disp([ 'HOMOTOPY mode 1: computing step ' int2str(i-1) '/' int2str(step_nbr) '...' ])
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old_params = M.params;
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old_exo = oo.exo_steady_state;
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old_exo_det = oo.exo_det_steady_state;
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M.params(values(ip,2)) = points(ip,i);
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oo.exo_steady_state(values(ix,2)) = points(ix,i);
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oo.exo_det_steady_state(values(ixd,2)) = points(ixd,i);
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[steady_state,M.params,info] = evaluate_steady_state(oo.steady_state,M,options,oo,~options.steadystate.nocheck);
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if info(1) == 0
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% if homotopy step is not successful, current values of steady
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% state are not modified
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oo.steady_state = steady_state;
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else
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M.params = old_params;
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oo.exo_steady_state = old_exo;
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oo.exo_det_steady_state = old_exo_det;
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break
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end
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end
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@ -1,105 +0,0 @@
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function homotopy2(values, step_nbr)
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% function homotopy2(values, step_nbr)
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%
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% Implements homotopy (mode 2) for steady-state computation.
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% Only one parameter/exogenous is changed at a time.
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% Computation jumps to next variable only when current variable has been
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% brought to its final value.
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% Variables are processed in the order in which they appear in "values".
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% The problem is solved var_nbr*step_nbr times.
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%
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% INPUTS
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% values: a matrix with 4 columns, representing the content of
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% homotopy_setup block, with one variable per line.
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% Column 1 is variable type (1 for exogenous, 2 for
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% exogenous deterministic, 4 for parameters)
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% Column 2 is symbol integer identifier.
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% Column 3 is initial value, and column 4 is final value.
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% Column 3 can contain NaNs, in which case previous
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% initialization of variable will be used as initial value.
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% step_nbr: number of steps for homotopy
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%
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% OUTPUTS
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% none
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright © 2008-2022 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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global M_ oo_ options_
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nv = size(values, 1);
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oldvalues = values(:,3);
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% Initialize all variables with initial value, or the reverse...
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for i = 1:nv
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switch values(i,1)
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case 1
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if isnan(oldvalues(i))
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oldvalues(i) = oo_.exo_steady_state(values(i,2));
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else
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oo_.exo_steady_state(values(i,2)) = oldvalues(i);
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end
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case 2
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if isnan(oldvalues(i))
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oldvalues(i) = oo_.exo_det_steady_state(values(i,2));
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else
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oo_.exo_det_steady_state(values(i,2)) = oldvalues(i);
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end
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case 4
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if isnan(oldvalues(i))
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oldvalues(i) = M_.params(values(i,2));
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else
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M_.params(values(i,2)) = oldvalues(i);
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end
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otherwise
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error('HOMOTOPY mode 2: incorrect variable types specified')
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end
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end
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if any(oldvalues == values(:,4))
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error('HOMOTOPY mode 2: initial and final values should be different')
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end
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% Actually do the homotopy
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for i = 1:nv
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switch values(i,1)
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case 1
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varname = M_.exo_names{values(i,2)};
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case 2
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varname = M_.exo_det_names{values(i,2)};
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case 4
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varname = M_.param_names{values(i,2)};
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end
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for v = oldvalues(i):(values(i,4)-oldvalues(i))/step_nbr:values(i,4)
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switch values(i,1)
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case 1
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oo_.exo_steady_state(values(i,2)) = v;
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case 2
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oo_.exo_det_steady_state(values(i,2)) = v;
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case 4
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M_.params(values(i,2)) = v;
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end
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disp([ 'HOMOTOPY mode 2: lauching solver with ' varname ' = ' num2str(v) ' ...'])
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oo_.steady_state = evaluate_steady_state(oo_.steady_state,M_,options_,oo_,~options_.steadystate.nocheck);
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end
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end
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@ -1,145 +0,0 @@
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function [M,oo,info,ip,ix,ixd]=homotopy3(values, step_nbr, M, options, oo)
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% function homotopy3(values, step_nbr)
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%
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% Implements homotopy (mode 3) for steady-state computation.
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% Tries first the most extreme values. If it fails to compute the steady
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% state, the interval between initial and desired values is divided by two
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% for each parameter. Every time that it is impossible to find a steady
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% state, the previous interval is divided by two. When one succeed to find
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% a steady state, the previous interval is multiplied by two.
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%
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% INPUTS
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% values: a matrix with 4 columns, representing the content of
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% homotopy_setup block, with one variable per line.
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% Column 1 is variable type (1 for exogenous, 2 for
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% exogenous deterministic, 4 for parameters)
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% Column 2 is symbol integer identifier.
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% Column 3 is initial value, and column 4 is final value.
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% Column 3 can contain NaNs, in which case previous
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% initialization of variable will be used as initial value.
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% step_nbr: maximum number of steps to try before aborting
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% M struct of model parameters
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% options struct of options
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% oo struct of outputs
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%
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% OUTPUTS
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% M struct of model parameters
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% oo struct of outputs
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% info return status 0: OK, 1: failed
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% ip index of parameters
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% ix index of exogenous variables
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% ixp index of exogenous deterministic variables
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright © 2008-2017 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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info = [];
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tol = 1e-8;
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nv = size(values,1);
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ip = find(values(:,1) == 4); % Parameters
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ix = find(values(:,1) == 1); % Exogenous
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ixd = find(values(:,1) == 2); % Exogenous deterministic
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if length([ip; ix; ixd]) ~= nv
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error('HOMOTOPY mode 3: incorrect variable types specified')
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end
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% Construct vector of starting values, using previously initialized values
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% when initial value has not been given in homotopy_setup block
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last_values = values(:,3);
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ipn = find(values(:,1) == 4 & isnan(last_values));
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last_values(ipn) = M.params(values(ipn, 2));
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ixn = find(values(:,1) == 1 & isnan(last_values));
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last_values(ixn) = oo.exo_steady_state(values(ixn, 2));
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ixdn = find(values(:,1) == 2 & isnan(last_values));
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last_values(ixdn) = oo.exo_det_steady_state(values(ixdn, 2));
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targetvalues = values(:,4);
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%if min(abs(targetvalues - last_values)) < tol
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% error('HOMOTOPY mode 3: distance between initial and final values should be at least %e for all variables', tol)
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%end
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iplus = find(targetvalues > last_values);
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iminus = find(targetvalues < last_values);
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curvalues = last_values;
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inc = (targetvalues-last_values)/2;
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kplus = [];
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kminus = [];
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last_values = [];
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disp('HOMOTOPY mode 3: launching solver at initial point...')
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iter = 1;
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while iter <= step_nbr
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M.params(values(ip,2)) = curvalues(ip);
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oo.exo_steady_state(values(ix,2)) = curvalues(ix);
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oo.exo_det_steady_state(values(ixd,2)) = curvalues(ixd);
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old_ss = oo.steady_state;
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[steady_state,params,info] = evaluate_steady_state(old_ss,M,options,oo,~options.steadystate.nocheck);
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if info(1) == 0
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oo.steady_state = steady_state;
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M.params = params;
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if length([kplus; kminus]) == nv
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return
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end
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if iter == 1
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disp('HOMOTOPY mode 3: successful step, now jumping to final point...')
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else
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disp('HOMOTOPY mode 3: successful step, now multiplying increment by 2...')
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end
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last_values = curvalues;
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old_params = params;
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old_exo_steady_state = oo.exo_steady_state;
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old_exo_det_steady_state = oo.exo_det_steady_state;
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inc = 2*inc;
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elseif iter == 1
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error('HOMOTOPY mode 3: can''t solve the model at 1st iteration')
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else
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disp('HOMOTOPY mode 3: failed step, now dividing increment by 2...')
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inc = inc/2;
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oo.steady_state = old_ss;
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end
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curvalues = last_values + inc;
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kplus = find(curvalues(iplus) >= targetvalues(iplus));
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curvalues(iplus(kplus)) = targetvalues(iplus(kplus));
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kminus = find(curvalues(iminus) <= targetvalues(iminus));
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curvalues(iminus(kminus)) = targetvalues(iminus(kminus));
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if max(abs(inc)) < tol
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disp('HOMOTOPY mode 3: failed, increment has become too small')
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M.params = old_params;
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oo.exo_steady_state = old_exo_steady_state;
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oo.exo_det_steady_state = old_exo_det_steady_state;
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return
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end
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iter = iter + 1;
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end
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disp('HOMOTOPY mode 3: failed, maximum iterations reached')
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M.params = old_params;
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oo.exo_steady_state = old_exo_steady_state;
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oo.exo_det_steady_state = old_exo_det_steady_state;
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288
matlab/steady.m
288
matlab/steady.m
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@ -11,7 +11,7 @@ function steady()
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% SPECIAL REQUIREMENTS
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% none
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% Copyright © 2001-2022 Dynare Team
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% Copyright © 2001-2023 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -103,3 +103,289 @@ else
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end
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M_.Sigma_e = Sigma_e;
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function [M,oo,info,ip,ix,ixd] = homotopy1(values, step_nbr, M, options, oo)
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% Implements homotopy (mode 1) for steady-state computation.
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% The multi-dimensional vector going from the set of initial values
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% to the set of final values is divided in as many sub-vectors as
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% there are steps, and the problem is solved as many times.
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%
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% INPUTS
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% values: a matrix with 4 columns, representing the content of
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% homotopy_setup block, with one variable per line.
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% Column 1 is variable type (1 for exogenous, 2 for
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% exogenous deterministic, 4 for parameters)
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% Column 2 is symbol integer identifier.
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% Column 3 is initial value, and column 4 is final value.
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% Column 3 can contain NaNs, in which case previous
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% initialization of variable will be used as initial value.
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% step_nbr: number of steps for homotopy
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% M struct of model parameters
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% options struct of options
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% oo struct of outputs
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%
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% OUTPUTS
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% M struct of model parameters
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% oo struct of outputs
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% ip index of parameters
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% ix index of exogenous variables
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% ixp index of exogenous deterministic variables
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nv = size(values, 1);
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ip = find(values(:,1) == 4); % Parameters
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ix = find(values(:,1) == 1); % Exogenous
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ixd = find(values(:,1) == 2); % Exogenous deterministic
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if length([ip; ix; ixd]) ~= nv
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error('HOMOTOPY mode 1: incorrect variable types specified')
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end
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% Construct vector of starting values, using previously initialized values
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% when initial value has not been given in homotopy_setup block
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oldvalues = values(:,3);
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ipn = find(values(:,1) == 4 & isnan(oldvalues));
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oldvalues(ipn) = M.params(values(ipn, 2));
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ixn = find(values(:,1) == 1 & isnan(oldvalues));
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oldvalues(ixn) = oo.exo_steady_state(values(ixn, 2));
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ixdn = find(values(:,1) == 2 & isnan(oldvalues));
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oldvalues(ixdn) = oo.exo_det_steady_state(values(ixdn, 2));
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points = zeros(nv, step_nbr+1);
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for i = 1:nv
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if (oldvalues(i) ~= values(i, 4))
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points(i,:) = oldvalues(i):(values(i,4)-oldvalues(i))/step_nbr:values(i,4);
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else
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points(i,:) = values(i,4);
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end
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end
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for i=1:step_nbr+1
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disp([ 'HOMOTOPY mode 1: computing step ' int2str(i-1) '/' int2str(step_nbr) '...' ])
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old_params = M.params;
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old_exo = oo.exo_steady_state;
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old_exo_det = oo.exo_det_steady_state;
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M.params(values(ip,2)) = points(ip,i);
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oo.exo_steady_state(values(ix,2)) = points(ix,i);
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oo.exo_det_steady_state(values(ixd,2)) = points(ixd,i);
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[steady_state,M.params,info] = evaluate_steady_state(oo.steady_state,M,options,oo,~options.steadystate.nocheck);
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if info(1) == 0
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% if homotopy step is not successful, current values of steady
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||||
% state are not modified
|
||||
oo.steady_state = steady_state;
|
||||
else
|
||||
M.params = old_params;
|
||||
oo.exo_steady_state = old_exo;
|
||||
oo.exo_det_steady_state = old_exo_det;
|
||||
break
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
function homotopy2(values, step_nbr)
|
||||
% Implements homotopy (mode 2) for steady-state computation.
|
||||
% Only one parameter/exogenous is changed at a time.
|
||||
% Computation jumps to next variable only when current variable has been
|
||||
% brought to its final value.
|
||||
% Variables are processed in the order in which they appear in "values".
|
||||
% The problem is solved var_nbr*step_nbr times.
|
||||
%
|
||||
% INPUTS
|
||||
% values: a matrix with 4 columns, representing the content of
|
||||
% homotopy_setup block, with one variable per line.
|
||||
% Column 1 is variable type (1 for exogenous, 2 for
|
||||
% exogenous deterministic, 4 for parameters)
|
||||
% Column 2 is symbol integer identifier.
|
||||
% Column 3 is initial value, and column 4 is final value.
|
||||
% Column 3 can contain NaNs, in which case previous
|
||||
% initialization of variable will be used as initial value.
|
||||
% step_nbr: number of steps for homotopy
|
||||
|
||||
global M_ oo_ options_
|
||||
|
||||
nv = size(values, 1);
|
||||
|
||||
oldvalues = values(:,3);
|
||||
|
||||
% Initialize all variables with initial value, or the reverse...
|
||||
for i = 1:nv
|
||||
switch values(i,1)
|
||||
case 1
|
||||
if isnan(oldvalues(i))
|
||||
oldvalues(i) = oo_.exo_steady_state(values(i,2));
|
||||
else
|
||||
oo_.exo_steady_state(values(i,2)) = oldvalues(i);
|
||||
end
|
||||
case 2
|
||||
if isnan(oldvalues(i))
|
||||
oldvalues(i) = oo_.exo_det_steady_state(values(i,2));
|
||||
else
|
||||
oo_.exo_det_steady_state(values(i,2)) = oldvalues(i);
|
||||
end
|
||||
case 4
|
||||
if isnan(oldvalues(i))
|
||||
oldvalues(i) = M_.params(values(i,2));
|
||||
else
|
||||
M_.params(values(i,2)) = oldvalues(i);
|
||||
end
|
||||
otherwise
|
||||
error('HOMOTOPY mode 2: incorrect variable types specified')
|
||||
end
|
||||
end
|
||||
|
||||
if any(oldvalues == values(:,4))
|
||||
error('HOMOTOPY mode 2: initial and final values should be different')
|
||||
end
|
||||
|
||||
% Actually do the homotopy
|
||||
for i = 1:nv
|
||||
switch values(i,1)
|
||||
case 1
|
||||
varname = M_.exo_names{values(i,2)};
|
||||
case 2
|
||||
varname = M_.exo_det_names{values(i,2)};
|
||||
case 4
|
||||
varname = M_.param_names{values(i,2)};
|
||||
end
|
||||
for v = oldvalues(i):(values(i,4)-oldvalues(i))/step_nbr:values(i,4)
|
||||
switch values(i,1)
|
||||
case 1
|
||||
oo_.exo_steady_state(values(i,2)) = v;
|
||||
case 2
|
||||
oo_.exo_det_steady_state(values(i,2)) = v;
|
||||
case 4
|
||||
M_.params(values(i,2)) = v;
|
||||
end
|
||||
|
||||
disp([ 'HOMOTOPY mode 2: lauching solver with ' varname ' = ' num2str(v) ' ...'])
|
||||
|
||||
oo_.steady_state = evaluate_steady_state(oo_.steady_state,M_,options_,oo_,~options_.steadystate.nocheck);
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
function [M,oo,info,ip,ix,ixd] = homotopy3(values, step_nbr, M, options, oo)
|
||||
% Implements homotopy (mode 3) for steady-state computation.
|
||||
% Tries first the most extreme values. If it fails to compute the steady
|
||||
% state, the interval between initial and desired values is divided by two
|
||||
% for each parameter. Every time that it is impossible to find a steady
|
||||
% state, the previous interval is divided by two. When one succeed to find
|
||||
% a steady state, the previous interval is multiplied by two.
|
||||
%
|
||||
% INPUTS
|
||||
% values: a matrix with 4 columns, representing the content of
|
||||
% homotopy_setup block, with one variable per line.
|
||||
% Column 1 is variable type (1 for exogenous, 2 for
|
||||
% exogenous deterministic, 4 for parameters)
|
||||
% Column 2 is symbol integer identifier.
|
||||
% Column 3 is initial value, and column 4 is final value.
|
||||
% Column 3 can contain NaNs, in which case previous
|
||||
% initialization of variable will be used as initial value.
|
||||
% step_nbr: maximum number of steps to try before aborting
|
||||
% M struct of model parameters
|
||||
% options struct of options
|
||||
% oo struct of outputs
|
||||
%
|
||||
% OUTPUTS
|
||||
% M struct of model parameters
|
||||
% oo struct of outputs
|
||||
% info return status 0: OK, 1: failed
|
||||
% ip index of parameters
|
||||
% ix index of exogenous variables
|
||||
% ixp index of exogenous deterministic variables
|
||||
|
||||
info = [];
|
||||
tol = 1e-8;
|
||||
|
||||
nv = size(values,1);
|
||||
|
||||
ip = find(values(:,1) == 4); % Parameters
|
||||
ix = find(values(:,1) == 1); % Exogenous
|
||||
ixd = find(values(:,1) == 2); % Exogenous deterministic
|
||||
|
||||
if length([ip; ix; ixd]) ~= nv
|
||||
error('HOMOTOPY mode 3: incorrect variable types specified')
|
||||
end
|
||||
|
||||
% Construct vector of starting values, using previously initialized values
|
||||
% when initial value has not been given in homotopy_setup block
|
||||
last_values = values(:,3);
|
||||
ipn = find(values(:,1) == 4 & isnan(last_values));
|
||||
last_values(ipn) = M.params(values(ipn, 2));
|
||||
ixn = find(values(:,1) == 1 & isnan(last_values));
|
||||
last_values(ixn) = oo.exo_steady_state(values(ixn, 2));
|
||||
ixdn = find(values(:,1) == 2 & isnan(last_values));
|
||||
last_values(ixdn) = oo.exo_det_steady_state(values(ixdn, 2));
|
||||
|
||||
targetvalues = values(:,4);
|
||||
|
||||
%if min(abs(targetvalues - last_values)) < tol
|
||||
% error('HOMOTOPY mode 3: distance between initial and final values should be at least %e for all variables', tol)
|
||||
%end
|
||||
iplus = find(targetvalues > last_values);
|
||||
iminus = find(targetvalues < last_values);
|
||||
|
||||
curvalues = last_values;
|
||||
inc = (targetvalues-last_values)/2;
|
||||
kplus = [];
|
||||
kminus = [];
|
||||
last_values = [];
|
||||
|
||||
disp('HOMOTOPY mode 3: launching solver at initial point...')
|
||||
|
||||
iter = 1;
|
||||
while iter <= step_nbr
|
||||
|
||||
M.params(values(ip,2)) = curvalues(ip);
|
||||
oo.exo_steady_state(values(ix,2)) = curvalues(ix);
|
||||
oo.exo_det_steady_state(values(ixd,2)) = curvalues(ixd);
|
||||
|
||||
old_ss = oo.steady_state;
|
||||
|
||||
[steady_state,params,info] = evaluate_steady_state(old_ss,M,options,oo,~options.steadystate.nocheck);
|
||||
if info(1) == 0
|
||||
oo.steady_state = steady_state;
|
||||
M.params = params;
|
||||
if length([kplus; kminus]) == nv
|
||||
return
|
||||
end
|
||||
if iter == 1
|
||||
disp('HOMOTOPY mode 3: successful step, now jumping to final point...')
|
||||
else
|
||||
disp('HOMOTOPY mode 3: successful step, now multiplying increment by 2...')
|
||||
end
|
||||
last_values = curvalues;
|
||||
old_params = params;
|
||||
old_exo_steady_state = oo.exo_steady_state;
|
||||
old_exo_det_steady_state = oo.exo_det_steady_state;
|
||||
inc = 2*inc;
|
||||
elseif iter == 1
|
||||
error('HOMOTOPY mode 3: can''t solve the model at 1st iteration')
|
||||
else
|
||||
disp('HOMOTOPY mode 3: failed step, now dividing increment by 2...')
|
||||
inc = inc/2;
|
||||
oo.steady_state = old_ss;
|
||||
end
|
||||
|
||||
curvalues = last_values + inc;
|
||||
kplus = find(curvalues(iplus) >= targetvalues(iplus));
|
||||
curvalues(iplus(kplus)) = targetvalues(iplus(kplus));
|
||||
kminus = find(curvalues(iminus) <= targetvalues(iminus));
|
||||
curvalues(iminus(kminus)) = targetvalues(iminus(kminus));
|
||||
|
||||
if max(abs(inc)) < tol
|
||||
disp('HOMOTOPY mode 3: failed, increment has become too small')
|
||||
M.params = old_params;
|
||||
oo.exo_steady_state = old_exo_steady_state;
|
||||
oo.exo_det_steady_state = old_exo_det_steady_state;
|
||||
return
|
||||
end
|
||||
|
||||
iter = iter + 1;
|
||||
end
|
||||
disp('HOMOTOPY mode 3: failed, maximum iterations reached')
|
||||
M.params = old_params;
|
||||
oo.exo_steady_state = old_exo_steady_state;
|
||||
oo.exo_det_steady_state = old_exo_det_steady_state;
|
||||
|
|
|
|||
Loading…
Reference in New Issue