121 lines
4.3 KiB
Matlab
121 lines
4.3 KiB
Matlab
function [PostMode, HessianMatrix, Scale, ModeValue] = gmhmaxlik(fun, xinit, Hinit, iscale, bounds, priorstd, gmhmaxlikOptions, OptimizationOptions, varargin)
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% Copyright © 2006-2017 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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% Set default options
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if ~isempty(Hinit)
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gmhmaxlikOptions.varinit = 'previous';
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else
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gmhmaxlikOptions.varinit = 'prior';
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end
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if ~isempty(OptimizationOptions)
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DynareOptionslist = read_key_value_string(OptimizationOptions);
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for i=1:rows(DynareOptionslist)
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switch DynareOptionslist{i,1}
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case 'NumberOfMh'
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gmhmaxlikOptions.iterations = DynareOptionslist{i,2};
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case 'ncov-mh'
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gmhmaxlikOptions.number = DynareOptionslist{i,2};
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case 'nscale-mh'
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gmhmaxlikOptions.nscale = DynareOptionslist{i,2};
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case 'nclimb-mh'
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gmhmaxlikOptions.nclimb = DynareOptionslist{i,2};
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case 'InitialCovarianceMatrix'
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switch DynareOptionslist{i,2}
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case 'previous'
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if isempty(Hinit)
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error('gmhmaxlik: No previous estimate of the Hessian matrix available! You cannot use the InitialCovarianceMatrix option!')
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else
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gmhmaxlikOptions.varinit = 'previous';
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end
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case {'prior', 'identity'}
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gmhmaxlikOptions.varinit = DynareOptionslist{i,2};
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otherwise
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error('gmhmaxlik: Unknown value for option ''InitialCovarianceMatrix''!')
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end
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case 'AcceptanceRateTarget'
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gmhmaxlikOptions.target = DynareOptionslist{i,2};
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if gmhmaxlikOptions.target>1 || gmhmaxlikOptions.target<eps
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error('gmhmaxlik: The value of option AcceptanceRateTarget should be a double between 0 and 1!')
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end
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otherwise
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warning(['gmhmaxlik: Unknown option (' DynareOptionslist{i,1} ')!'])
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end
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end
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end
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% Evaluate the objective function.
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OldModeValue = feval(fun,xinit,varargin{:});
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if ~exist('MeanPar','var')
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MeanPar = xinit;
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end
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switch gmhmaxlikOptions.varinit
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case 'previous'
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CovJump = inv(Hinit);
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case 'prior'
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% The covariance matrix is initialized with the prior
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% covariance (a diagonal matrix) %%Except for infinite variances ;-)
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stdev = priorstd;
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indx = find(isinf(stdev));
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stdev(indx) = ones(length(indx),1)*sqrt(10);
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vars = stdev.^2;
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CovJump = diag(vars);
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case 'identity'
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vars = ones(length(priorstd),1)*0.1;
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CovJump = diag(vars);
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otherwise
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error('gmhmaxlik: This is a bug! Please contact the developers.')
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end
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OldPostVariance = CovJump;
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OldPostMean = xinit;
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OldPostMode = xinit;
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Scale = iscale;
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for i=1:gmhmaxlikOptions.iterations
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if i<gmhmaxlikOptions.iterations
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flag = '';
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else
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flag = 'LastCall';
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end
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[PostMode, PostVariance, Scale, PostMean] = gmhmaxlik_core(fun, OldPostMode, bounds, gmhmaxlikOptions, Scale, flag, MeanPar, OldPostVariance, varargin{:});
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ModeValue = feval(fun, PostMode, varargin{:});
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dVariance = max(max(abs(PostVariance-OldPostVariance)));
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dMean = max(abs(PostMean-OldPostMean));
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skipline()
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printline(58,'=')
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disp([' Change in the posterior covariance matrix = ' num2str(dVariance) '.'])
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disp([' Change in the posterior mean = ' num2str(dMean) '.'])
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disp([' Current mode = ' num2str(ModeValue)])
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disp([' Mode improvement = ' num2str(abs(OldModeValue-ModeValue))])
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disp([' New value of jscale = ' num2str(Scale)])
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printline(58,'=')
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OldModeValue = ModeValue;
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OldPostMean = PostMean;
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OldPostVariance = PostVariance;
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end
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HessianMatrix = inv(PostVariance);
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skipline()
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disp(['Optimal value of the scale parameter = ' num2str(Scale)])
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skipline() |