From ea271e7e843cd7fde236ca83c4ed13b51c08756d Mon Sep 17 00:00:00 2001
From: michel <michel@ac1d8469-bf42-47a9-8791-bf33cf982152>
Date: Sun, 14 Sep 2008 15:38:23 +0000
Subject: [PATCH] added missing function

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@2066 ac1d8469-bf42-47a9-8791-bf33cf982152
---
 matlab/simultxdet.m | 141 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 141 insertions(+)
 create mode 100644 matlab/simultxdet.m

diff --git a/matlab/simultxdet.m b/matlab/simultxdet.m
new file mode 100644
index 000000000..a7c5a7b2b
--- /dev/null
+++ b/matlab/simultxdet.m
@@ -0,0 +1,141 @@
+% Copyright (C) 2005 Michel Juillard
+%
+
+function [y_,int_width]=simultexdet(y0,ex,ex_det, iorder,var_list,M_,oo_,options_)
+%  global endo_nbr ykmin_ xkmin_ it_ options_ iy_ M_ exe_det_ Sigma_e_ lgy_
+
+  dr = oo_.dr;
+  ykmin = M_.maximum_lag;
+  endo_nbr = M_.endo_nbr;
+  exo_det_steady_state = oo_.exo_det_steady_state;
+  nstatic = dr.nstatic;
+  npred =dr.npred;
+  nc = size(dr.ghx,2);
+  iter = size(ex,1);
+  nx = size(dr.ghu,2);
+  y_ = zeros(size(y0,1),iter+ykmin);
+  y_(:,1:ykmin) = y0;
+  k1 = [ykmin:-1:1];
+  k2 = dr.kstate(find(dr.kstate(:,2) <= ykmin+1),[1 2]);
+  k2 = k2(:,1)+(ykmin+1-k2(:,2))*endo_nbr;
+  k3 = M_.lead_lag_incidence(1:ykmin,:)';
+  k3 = find(k3(:));
+  k4 = dr.kstate(find(dr.kstate(:,2) < ykmin+1),[1 2]);
+  k4 = k4(:,1)+(ykmin+1-k4(:,2))*endo_nbr;
+  
+  if options_.simul_algo == 1
+    o1 = dr.nstatic+1;
+    o2 = dr.nstatic+dr.npred;
+    o3 = o2-dr.nboth+1;
+    [junk, k5] = sort(dr.order_var(o1:o2));
+    [junk, k6] = sort(dr.order_var(o3:end));
+  end
+  
+  nvar = size(var_list,1);
+  if nvar == 0
+    nvar = endo_nbr;
+    ivar = [1:nvar];
+  else
+    ivar=zeros(nvar,1);
+    for i=1:nvar
+      i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
+      if isempty(i_tmp)
+	disp(var_list(i,:));
+	error (['One of the variable specified does not exist']) ;
+      else
+	ivar(i) = i_tmp;
+      end
+    end
+  end
+
+  if iorder == 1
+    for i = ykmin+1: iter+ykmin
+      tempx1 = y_(dr.order_var,k1);
+      tempx2 = tempx1-repmat(dr.ys(dr.order_var),1,ykmin);
+      tempx = tempx2(k2);
+      if options_.simul_algo == 0
+	y_(dr.order_var,i) = dr.ys(dr.order_var)+dr.ghx*tempx+dr.ghu* ...
+	    ex(i,:)';
+	for j=1:min(ykmin+M_.exo_det_length+1-i,M_.exo_det_length)
+	  y_(dr.order_var,i) = y_(dr.order_var,i) + dr.ghud{j}*(ex_det(i+j-1,:)'-exo_det_steady_state');
+	end
+      elseif options_.simul_algo == 1
+	it_ = i;
+	m = dr.ys(dr.order_var);
+	[y_(:,i), check] = dynare_solve('ff_simul1',y_(:,i-1),tempx1(k3), ...
+					m(o3:end),tempx(k4),o1,o2,o3,k6);
+      end
+	
+      k1 = k1+1;
+    end
+  elseif iorder == 2
+    for i = ykmin+1: iter+ykmin
+      tempx1 = y_(dr.order_var,k1);
+      tempx2 = tempx1-repmat(dr.ys(dr.order_var),1,ykmin);
+      tempx = tempx2(k2);
+      tempu = ex(i-ykmin,:)';
+      tempuu = kron(tempu,tempu);
+      if options_.simul_algo == 0
+	tempxx = kron(tempx,tempx);
+	tempxu = kron(tempx,tempu);
+	y_(dr.order_var,i) = dr.ys(dr.order_var)+dr.ghs2/2+dr.ghx*tempx+ ...
+	    dr.ghu*tempu+0.5*(dr.ghxx*tempxx+dr.ghuu*tempuu)+dr.ghxu* ...
+	    tempxu;
+	for j=1:min(ykmin+M_.exo_det_length+1-i,M_.exo_det_length)
+	  tempud = ex_det(i+j-1,:)'-exo_det_steady_state;
+	  tempudud = kron(tempud,tempud);
+	  tempxud = kron(tempx,tempud);
+	  tempuud = kron(tempu,tempud);
+	  y_(dr.order_var,i) = y_(dr.order_var,i) + dr.ghud{j}*tempud + ...
+	      dr.ghxud{j}*tempxud + dr.ghuud{j}*tempuud + ...
+	      0.5*dr.ghudud{j,j}*tempudud;
+	  for k=1:j-1
+	    tempudk = ex_det(i+k-1,:)'-exo_det_steady_state;
+	    tempududk = kron(tempudk,tempud);
+	    y_(dr.order_var,i) = y_(dr.order_var,i) + ...
+		dr.ghudud{k,j}*tempududk;
+	  end
+	end
+      elseif options_.simul_algo == 1
+	it_ = i;
+	m = dr.ys(dr.order_var)+dr.ghs2/2;
+	tempx1 = y_(:,k1);
+	[y_(:,i), check] = dynare_solve('ff_simul2',y_(:,i-1),tempx1(k3), ...
+					m(o3:end),tempx(k4),o1,o2,o3,k6);
+      end
+      k1 = k1+1;
+    end
+  end
+
+  [A,B] = kalman_transition_matrix(dr,nstatic+(1:npred),1:nc,dr.transition_auxiliary_variables,M_.exo_nbr);
+  
+  sigma_u = B*M_.Sigma_e*B';
+  sigma_y = 0;
+  
+  for i=1:iter
+    var_yf(i,dr.order_var) = diag(sigma_y(1:endo_nbr,1:endo_nbr))';
+    if i == iter
+      break
+    end
+    sigma_u = A*sigma_u*A';
+    sigma_y = sigma_y+sigma_u;
+  end
+
+  fact = qnorm((1-options_.conf_sig)/2,0,1);
+  
+  int_width = zeros(iter,endo_nbr);
+  for i=1:endo_nbr
+    int_width(:,i) = fact*sqrt(var_yf(:,i));
+  end
+  
+  for i=1:nvar
+    my_subplot(i,nvar,2,3,'Forecasts');
+    
+    plot([-ykmin+1:0],y0(ivar(i),1:ykmin),'b-',...
+	 [1:iter],y_(ivar(i),ykmin+1:end),'g-',...
+	 [1:iter],y_(ivar(i),ykmin+1:end)'+int_width(:,ivar(i)),'g:',...
+	 [1:iter],y_(ivar(i),ykmin+1:end)'-int_width(:,ivar(i)),'g:',...
+	 [1 iter],repmat(dr.ys(ivar(i)),1,2),'r-');
+    title(M_.endo_names(ivar(i),:));
+  end
+