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var_forecast: update writing following change in 9888881d1ccc8d748d1f9cd7f462b5fa30f8bac3

time-shift
Houtan Bastani 2016-11-29 17:13:40 +01:00 committed by Stéphane Adjemian (Charybdis)
parent 476a8a27cc
commit e205c8813f
1 changed files with 33 additions and 11 deletions
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44
matlab/writeVarExpectationFunction.m
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@ -26,21 +26,43 @@ fprintf(fid, '%%%% Construct y\n');
fprintf(fid, 'assert(length(y) == %d);\n', sum(sum(M_.lead_lag_incidence ~= 0)));
endo_names = cellstr(M_.endo_names);
idxlen = length(M_.var.(var_model_name).var_list_);
yidx = zeros(idxlen, 1);
for i=1:idxlen
yidx(i) = find(strcmp(strtrim(M_.var.(var_model_name).var_list_(i,:)), endo_names));
nvars = length(M_.var.(var_model_name).var_list_);
var_model_order = M_.var.(var_model_name).order;
yidx = zeros(nvars, min(var_model_order, 2));
% first for order <= 2, drawing variables directly from their endo_names
for i=1:min(var_model_order, 2)
if mod(i, 2) == 0
ridx = 1;
else
ridx = 2;
end
for j=1:nvars
yidx(j, i) = M_.lead_lag_incidence(ridx, strcmp(strtrim(M_.var.(var_model_name).var_list_(j,:)), endo_names)');
end
end
yidx = yidx(:);
% then for order > 2
if var_model_order > 2
y1idx = zeros((var_model_order - 2)*nvars, var_model_order - 2);
for i=3:var_model_order
for j=1:nvars
varidx = [M_.aux_vars.orig_index] == find(strcmp(strtrim(M_.var.(var_model_name).var_list_(j,:)), endo_names)) ...
& [M_.aux_vars.orig_lead_lag] == -i;
cidx = [M_.aux_vars.endo_index];
cidx = cidx(varidx);
y1idx(j, i-2) = M_.lead_lag_incidence(2, cidx);
end
end
yidx = [yidx ; y1idx(:)];
end
fprintf(fid, 'y = y([');
fprintf(fid, '%d ', yidx);
fprintf(fid, '], :);\n');
fprintf(fid, ']);\n');
lm = length(mu);
lc = length(autoregressive_matrices);
assert(lc == M_.var.(var_model_name).order);
fprintf(fid, 'if size(y, 1) ~= %d || size(y, 2) ~= %d\n', lm, M_.var.(var_model_name).order);
fprintf(fid, ' error(''The dimensions of y are not correct. It should be an nvars x order matrix'');\n');
fprintf(fid, 'end\n');
assert(lc == var_model_order);
A = zeros(lm*lc, lm*lc);
for i=1:lc
@ -53,8 +75,8 @@ for i=1:lc
A(lm*i+1:lm*i+lm, col) = eye(lm, lm);
end
end
if M_.var.(var_model_name).order > 1
mu = [mu; zeros(lm*M_.var.(var_model_name).order-lm, 1)];
if var_model_order > 1
mu = [mu; zeros(lm*var_model_order-lm, 1)];
end
fprintf(fid, '\n%%%% Calculate %d-step-ahead forecast\n', max(horizon));
if max(horizon) == 1