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Fix some files which were not UTF-8 encoded

pac-components
Sébastien Villemot 2021-10-01 18:30:39 +02:00
parent 393f9e97c5
commit d9ca83f317
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GPG Key ID: 2CECE9350ECEBE4A
3 changed files with 6 additions and 6 deletions
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4
matlab/+mom/optimal_weighting_matrix.m
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@ -3,7 +3,7 @@ function W_opt = optimal_weighting_matrix(m_data, moments, q_lag)
% -------------------------------------------------------------------------
% This function computes the optimal weigthing matrix by a Bartlett kernel with maximum lag q_lag
% Adapted from replication codes of
% o Andreasen, Fernández-Villaverde, Rubio-Ramírez (2018): "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications", Review of Economic Studies, 85(1):1-49.
% o Andreasen, Fernández-Villaverde, Rubio-Ramírez (2018): "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications", Review of Economic Studies, 85(1):1-49.
% =========================================================================
% INPUTS
% o m_data [T x numMom] selected data moments at each point in time
@ -76,4 +76,4 @@ function GAMA_corr = Corr_Matrix(h_Func,T,num_Mom,v)
GAMA_corr = GAMA_corr + h_Func(t-v,:)'*h_Func(t,:);
end
GAMA_corr = GAMA_corr/T;
end
end

4
matlab/+mom/standard_errors.m
View File

@ -3,7 +3,7 @@ function [SE_values, Asympt_Var] = standard_errors(xparam, objective_function, B
% -------------------------------------------------------------------------
% This function computes standard errors to the method of moments estimates
% Adapted from replication codes of
% o Andreasen, Fernández-Villaverde, Rubio-Ramírez (2018): "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications", Review of Economic Studies, 85(1):1-49.
% o Andreasen, Fernández-Villaverde, Rubio-Ramírez (2018): "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications", Review of Economic Studies, 85(1):1-49.
% =========================================================================
% INPUTS
% o xparam: value of estimated parameters as returned by set_prior()
@ -115,4 +115,4 @@ else
Asympt_Var = 1/T*AA*D'*WW*S*WW*D*AA;
end
SE_values = sqrt(diag(Asympt_Var));
SE_values = sqrt(diag(Asympt_Var));

4
matlab/writeVarExpectationFunction.m
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@ -129,7 +129,7 @@ if var_model_order > 1
mu = [mu; zeros(lm*var_model_order-lm, 1)];
end
fprintf(fid, '\n%%%% Calculate %d-step-ahead forecast for VAR(%d) written as VAR(1)\n', max(horizon), var_model_order);
fprintf(fid, '%% Follows Lütkepohl (2005) pg 15 & 34\n');
fprintf(fid, '%% Follows Lütkepohl (2005) pg 15 & 34\n');
if max(horizon) == 1
printInsideOfLoop(fid, mu, A, false);
fprintf(fid, 'ret(1, :) = y(1:%d);\n', lm);
@ -179,4 +179,4 @@ fprintf(fid, '%sy = ...\n%s[ ... %% intercept\n%s', fs, spaces, ns);
fprintf(fid, ' ] + ...\n%s[ ... %% autoregressive matrices\n%s', spaces, ns);
fprintf(fid, [repmat('% f ', 1, size(A, 2)) '; ...\n' ns], A');
fprintf(fid, ' ] * y;\n');
end
end