135 lines
5.5 KiB
Matlab
135 lines
5.5 KiB
Matlab
function swz_write_markov_file(fname,M,options)
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n_chains = length(options.ms.ms_chain);
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nvars = size(options.varobs,1);
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fh = fopen(fname,'w');
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%/******************************************************************************/
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%/********************* Markov State Variable Information **********************/
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%/******************************************************************************/
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fprintf(fh,'//== Flat Independent Markov States and Simple Restrictions ==//\n\n');
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%//This number is NOT used but read in.
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fprintf(fh,'//== Number Observations ==//\n');
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fprintf(fh,'0\n\n');
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fprintf(fh,'//== Number Independent State Variables ==//\n');
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fprintf(fh,'%d\n\n',n_chains);
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for i_chain = 1:n_chains
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%//=====================================================//
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%//== state_variable[i] (1 <= i <= n_state_variables) ==//
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%//=====================================================//
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fprintf(fh,'//== Number of states for state_variable[%d] ==//\n', ...
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i_chain);
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n_states = length(options.ms.ms_chain(i_chain).state);
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fprintf(fh,'%d\n\n',n_states);
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%//== 03/15/06: DW TVBVAR code reads the data below and overwrite the prior data read somewhere else if any.
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%//== Each column contains the parameters for a Dirichlet prior on the corresponding
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%//== column of the transition matrix. Each element must be positive. For each column,
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%//== the relative size of the prior elements determine the relative size of the elements
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%//== of the transition matrix and overall larger sizes implies a tighter prior.
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fprintf(fh,['//== Transition matrix prior for state_variable[%d]. ' ...
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'(n_states x n_states) ==//\n'],i_chain);
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Alpha = ones(n_states,n_states);
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for i_state = 1:n_states
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p = 1-1/options.ms.ms_chain(i_chain).state(i_state).duration;
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Alpha(i_state,i_state) = p*(n_states-1)/(1-p);
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fprintf(fh,'%22.16f',Alpha(i_state,:));
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fprintf(fh,'\n');
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end
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fprintf(fh,['\n//== Free Dirichet dimensions for state_variable[%d] ' ...
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'==//\n'],i_chain);
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% fprintf(fh,'%d ',repmat(n_states,1,n_states));
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fprintf(fh,'%d ',repmat(2,1,n_states));
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fprintf(fh,'\n\n');
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%//== The jth restriction matrix is n_states-by-free[j]. Each row of the restriction
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%//== matrix has exactly one non-zero entry and the sum of each column must be one.
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fprintf(fh,['//== Column restrictions for state_variable[%d] ' ...
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'==//\n'],i_chain);
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for i_state = 1:n_states
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if i_state == 1
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M = eye(n_states,2);
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elseif i_state == n_states
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M = [zeros(n_states-2,2); eye(2)];
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else
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M = zeros(n_states,2);
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M(i_state+[-1 1],1) = ones(2,1)/2;
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M(i_state,2) = 1;
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end
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for j_state = 1:n_states
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fprintf(fh,'%d ',M(j_state,:));
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fprintf(fh,'\n');
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end
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fprintf(fh,'\n');
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end
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end
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%/******************************************************************************/
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%/******************************* VAR Parameters *******************************/
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%/******************************************************************************/
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%//NOT read
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fprintf(fh,'//== Number Variables ==//\n');
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fprintf(fh,'%d\n\n',nvars);
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%//NOT read
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fprintf(fh,'//== Number Lags ==//\n');
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fprintf(fh,'%d\n\n',options.ms.nlags);
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%//NOT read
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fprintf(fh,'//== Exogenous Variables ==//\n');
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fprintf(fh,'1\n\n');
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%//== nvar x n_state_variables matrix. In the jth row, a non-zero value implies that
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%this state variable controls the jth column of A0 and Aplus
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fprintf(fh,['//== Controlling states variables for coefficients ==//\' ...
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'n']);
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for i_var = 1:nvars
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for i_chain = 1:n_chains
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if ~isfield(options.ms.ms_chain(i_chain),'svar_coefficients') ...
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|| isempty(options.ms.ms_chain(i_chain).svar_coefficients)
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i_equations = 0;
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else
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i_equations = ...
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options.ms.ms_chain(i_chain).svar_coefficients.equations;
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end
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if strcmp(i_equations,'ALL') || any(i_equations == i_var)
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fprintf(fh,'%d ',1);
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else
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fprintf(fh,'%d ',0);
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end
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end
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fprintf(fh,'\n');
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end
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%//== nvar x n_state_variables matrix. In the jth row, a non-zero value implies that
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%this state variable controls the jth diagonal element of Xi
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fprintf(fh,'\n//== Controlling states variables for variance ==//\n');
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for i_var = 1:nvars
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for i_chain = 1:n_chains
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if ~isfield(options.ms.ms_chain(i_chain),'svar_variances') ...
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|| isempty(options.ms.ms_chain(i_chain).svar_variances)
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i_equations = 0;
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else
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i_equations = ...
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options.ms.ms_chain(i_chain).svar_variances.equations;
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end
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if strcmp(i_equations,'ALL') || any(i_equations == i_var)
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fprintf(fh,'%d ',1);
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else
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fprintf(fh,'%d ',0);
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end
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end
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fprintf(fh,'\n');
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end
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fclose(fh);
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