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v4 bug correction and correct smoother for new diffuse algorithm 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1682 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
michel 2008-01-30 21:32:20 +00:00
parent d01ed3ca16
commit 4443d56136
3 changed files with 79 additions and 16 deletions
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6
matlab/DiffuseKalmanSmoother3_Z.m
View File

@ -97,7 +97,7 @@ while newRank & t < smpl
v(i,t) = Y(i,t)-Zi*a(:,t);
Fstar(i,t) = Zi*Pstar(:,:,t)*Zi';
Finf(i,t) = Zi*Pinf(:,:,t)*Zi';
Kstar(:,i,t) = Pstar(:,:,t)*Zi;
Kstar(:,i,t) = Pstar(:,:,t)*Zi';
if Finf(i,t) > crit & newRank
icc=icc+1;
Kinf(:,i,t) = Pinf(:,:,t)*Zi';
@ -168,7 +168,7 @@ while notsteady & t<smpl
P(:,:,t)=tril(P(:,:,t))+tril(P(:,:,t),-1)';
P1(:,:,t) = P(:,:,t);
for i=1:pp
Zi = Z(i,:)'
Zi = Z(i,:);
v(i,t) = Y(i,t) - Zi*a(:,t);
Fi(i,t) = Zi*P(:,:,t)*Zi';
Ki(:,i,t) = P(:,:,t)*Zi';
@ -200,7 +200,7 @@ while t<smpl
t=t+1;
a1(:,t) = a(:,t);
for i=1:pp
Zi = Z(i,:)';
Zi = Z(i,:);
v(i,t) = Y(i,t) - Zi*a(:,t);
if Fi_s(i) > crit
a(:,t) = a(:,t) + Ki_s(:,i)*v(i,t)/Fi_s(i);

2
matlab/DiffuseLikelihood3_Z.m
View File

@ -149,7 +149,7 @@ while t < smpl
t = t+1;
Pstar = oldP;
for i=1:pp
Zi = Z(i,i);
Zi = Z(i,:);
v(i) = Y(i,t) - Zi*a;
Fi = Zi*Pstar*Zi';
if Fi > crit

87
matlab/DsgeSmoother.m
View File

@ -82,18 +82,71 @@ function [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK,T,R] = Dsge
Pstar = 10*eye(np);
Pinf = [];
elseif options_.lik_init == 3 % Diffuse Kalman filter
Pstar = zeros(np,np);
ivs = bayestopt_.var_list_stationary;
Pstar(ivs,ivs) = lyapunov_symm(T(ivs,ivs),R(ivs,:)*Q* ...
transpose(R(ivs,:)));
% Pinf = bayestopt_.Pinf;
% by M. Ratto
RR=T(:,find(~ismember([1:np],ivs)));
i=find(abs(RR)>1.e-10);
R0=zeros(size(RR));
R0(i)=sign(RR(i));
Pinf=R0*R0';
% by M. Ratto
if options_.kalman_algo < 4
Pstar = zeros(np,np);
ivs = bayestopt_.restrict_var_list_stationary;
R1 = R(ivs,:);
Pstar(ivs,ivs) = lyapunov_symm(T(ivs,ivs),R1*Q*R1');
% Pinf = bayestopt_.Pinf;
% by M. Ratto
RR=T(:,bayestopt_.restrict_var_list_nonstationary);
i=find(abs(RR)>1.e-10);
R0=zeros(size(RR));
R0(i)=sign(RR(i));
Pinf=R0*R0';
% by M. Ratto
else
[QT,ST] = schur(T);
e1 = abs(ordeig(ST)) > 2-options_.qz_criterium;
[QT,ST] = ordschur(QT,ST,e1);
k = find(abs(ordeig(ST)) > 2-options_.qz_criterium);
nk = length(k);
nk1 = nk+1;
Pinf = zeros(np,np);
Pinf(1:nk,1:nk) = eye(nk);
Pstar = zeros(np,np);
B = QT'*R*Q*R'*QT;
for i=np:-1:nk+2
if ST(i,i-1) == 0
if i == np
c = zeros(np-nk,1);
else
c = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i,i+1:end)')+...
ST(i,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i);
end
q = eye(i-nk)-ST(nk1:i,nk1:i)*ST(i,i);
Pstar(nk1:i,i) = q\(B(nk1:i,i)+c);
Pstar(i,nk1:i-1) = Pstar(nk1:i-1,i)';
else
if i == np
c = zeros(np-nk,1);
c1 = zeros(np-nk,1);
else
c = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i,i+1:end)')+...
ST(i,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i)+...
ST(i,i-1)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i-1);
c1 = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i-1,i+1:end)')+...
ST(i-1,i-1)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i-1)+...
ST(i-1,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i);
end
q = [eye(i-nk)-ST(nk1:i,nk1:i)*ST(i,i) -ST(nk1:i,nk1:i)*ST(i,i-1);...
-ST(nk1:i,nk1:i)*ST(i-1,i) eye(i-nk)-ST(nk1:i,nk1:i)*ST(i-1,i-1)];
z = q\[B(nk1:i,i)+c;B(nk1:i,i-1)+c1];
Pstar(nk1:i,i) = z(1:(i-nk));
Pstar(nk1:i,i-1) = z(i-nk+1:end);
Pstar(i,nk1:i-1) = Pstar(nk1:i-1,i)';
Pstar(i-1,nk1:i-2) = Pstar(nk1:i-2,i-1)';
i = i - 1;
end
end
if i == nk+2
c = ST(nk+1,:)*(Pstar(:,nk+2:end)*ST(nk1,nk+2:end)')+ST(nk1,nk1)*ST(nk1,nk+2:end)*Pstar(nk+2:end,nk1);
Pstar(nk1,nk1)=(B(nk1,nk1)+c)/(1-ST(nk1,nk1)*ST(nk1,nk1));
end
Z = QT(mf,:);
R1 = QT'*R;
end
end
% -----------------------------------------------------------------------------
% 4. Kalman smoother
@ -115,5 +168,15 @@ function [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK,T,R] = Dsge
end
elseif options_.kalman_algo == 3
[alphahat,etahat,ahat,aK] = DiffuseKalmanSmoother3(T,R,Q,Pinf,Pstar,Y,trend,nobs,np,smpl,mf);
elseif options_.kalman_algo == 4
data1 = Y - trend;
[alphahat,etahat,ahat,aK] = DiffuseKalmanSmoother1_Z(ST,Z,R1,Q,Pinf,Pstar,data1,nobs,np,smpl);
alphahat = QT*alphahat;
ahat = QT*ahat;
elseif options_.kalman_algo == 5
data1 = Y - trend;
[alphahat,etahat,ahat,aK] = DiffuseKalmanSmoother3_Z(ST,Z,R1,Q,Pinf,Pstar,data1,nobs,np,smpl);
alphahat = QT*alphahat;
ahat = QT*ahat;
end
end