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various bug fixes for filter and smoother with missing observations 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@2282 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
michel 2008-12-03 07:30:26 +00:00
parent 5bf9ed894c
commit bf65cb4f10
5 changed files with 64 additions and 60 deletions
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1
matlab/DiffuseKalmanSmoother3.m
View File

@ -74,6 +74,7 @@ end
Fstar = zeros(pp,smpl_diff);
Finf = zeros(pp,smpl_diff);
Fi = zeros(pp,smpl_diff);
Ki = zeros(mm,pp,smpl);
Li = zeros(mm,mm,pp,smpl);
Linf = zeros(mm,mm,pp,smpl_diff);

1
matlab/DiffuseKalmanSmoother3_Z.m
View File

@ -83,6 +83,7 @@ end
Fstar = zeros(pp,smpl_diff);
Finf = zeros(pp,smpl_diff);
Fi = zeros(pp,smpl_diff);
Ki = zeros(mm,pp,smpl);
Li = zeros(mm,mm,pp,smpl);
Linf = zeros(mm,mm,pp,smpl_diff);

2
matlab/kalman/likelihood/missing_observations_diffuse_kalman_filter.m
View File

@ -53,7 +53,7 @@ function [LIK, lik] = missing_observations_diffuse_kalman_filter(T,R,Q,H,Pinf,Ps
oldK = 0;
lik = zeros(smpl+1,1);
LIK = Inf;
lik(smpl+1) = number_of_observations*pp*log(2*pi);
lik(smpl+1) = number_of_observations*log(2*pi);
notsteady = 1;
reste = 0;

55
matlab/missing_DiffuseKalmanSmoother3.m
View File

@ -75,6 +75,7 @@ end
Fstar = zeros(pp,smpl_diff);
Finf = zeros(pp,smpl_diff);
Fi = zeros(pp,smpl_diff);
Ki = zeros(mm,pp,smpl);
Li = zeros(mm,mm,pp,smpl);
Linf = zeros(mm,mm,pp,smpl_diff);
@ -211,34 +212,34 @@ while notsteady & t<smpl
aK(jnk,:,t+jnk) = T^jnk*a(:,t);
end
P(:,:,t+1) = T*P(:,:,t)*transpose(T) + QQ;
notsteady = ~(max(max(abs(P(:,:,t+1)-P(:,:,t))))<crit);
end
P_s=tril(P(:,:,t))+transpose(tril(P(:,:,t),-1));
Fi_s = Fi(:,t);
Ki_s = Ki(:,:,t);
L_s =Li(:,:,:,t);
if t<smpl
t_steady = t+1;
P = cat(3,P(:,:,1:t),repmat(P(:,:,t),[1 1 smpl-t_steady+1]));
Fi = cat(2,Fi(:,1:t),repmat(Fi_s,[1 1 smpl-t_steady+1]));
Li = cat(4,Li(:,:,:,1:t),repmat(L_s,[1 1 smpl-t_steady+1]));
Ki = cat(3,Ki(:,:,1:t),repmat(Ki_s,[1 1 smpl-t_steady+1]));
end
while t<smpl
t=t+1;
a(:,t) = a1(:,t);
di = data_index{t}';
for i=di
v(i,t) = Y(i,t) - a(mf(i),t) - trend(i,t);
if Fi_s(i) > crit
a(:,t) = a(:,t) + Ki_s(:,i)*v(i,t)/Fi_s(i);
end
end
a1(:,t+1) = T*a(:,t);
for jnk=1:nk,
aK(jnk,:,t+jnk) = T^jnk*a(:,t);
end
% notsteady = ~(max(max(abs(P(:,:,t+1)-P(:,:,t))))<crit);
end
% $$$ P_s=tril(P(:,:,t))+transpose(tril(P(:,:,t),-1));
% $$$ Fi_s = Fi(:,t);
% $$$ Ki_s = Ki(:,:,t);
% $$$ L_s =Li(:,:,:,t);
% $$$ if t<smpl
% $$$ t_steady = t+1;
% $$$ P = cat(3,P(:,:,1:t),repmat(P(:,:,t),[1 1 smpl-t_steady+1]));
% $$$ Fi = cat(2,Fi(:,1:t),repmat(Fi_s,[1 1 smpl-t_steady+1]));
% $$$ Li = cat(4,Li(:,:,:,1:t),repmat(L_s,[1 1 smpl-t_steady+1]));
% $$$ Ki = cat(3,Ki(:,:,1:t),repmat(Ki_s,[1 1 smpl-t_steady+1]));
% $$$ end
% $$$ while t<smpl
% $$$ t=t+1;
% $$$ a(:,t) = a1(:,t);
% $$$ di = data_index{t}';
% $$$ for i=di
% $$$ v(i,t) = Y(i,t) - a(mf(i),t) - trend(i,t);
% $$$ if Fi_s(i) > crit
% $$$ a(:,t) = a(:,t) + Ki_s(:,i)*v(i,t)/Fi_s(i);
% $$$ end
% $$$ end
% $$$ a1(:,t+1) = T*a(:,t);
% $$$ for jnk=1:nk,
% $$$ aK(jnk,:,t+jnk) = T^jnk*a(:,t);
% $$$ end
% $$$ end
ri=zeros(mm,1);
t = smpl+1;
while t>d+1

65
matlab/missing_DiffuseKalmanSmoother3_Z.m
View File

@ -84,6 +84,7 @@ end
Fstar = zeros(pp,smpl_diff);
Finf = zeros(pp,smpl_diff);
Fi = zeros(pp,smpl);
Ki = zeros(mm,pp,smpl);
Li = zeros(mm,mm,pp,smpl);
Linf = zeros(mm,mm,pp,smpl_diff);
@ -214,39 +215,39 @@ while notsteady & t<smpl
PK(jnk,:,:,t+jnk) = Pf;
end
P(:,:,t+1) = T*P(:,:,t)*T' + QQ;
notsteady = ~(max(max(abs(P(:,:,t+1)-P(:,:,t))))<crit);
end
P_s=tril(P(:,:,t))+tril(P(:,:,t),-1)';
P1_s=tril(P1(:,:,t))+tril(P1(:,:,t),-1)';
Fi_s = Fi(:,t);
Ki_s = Ki(:,:,t);
L_s =Li(:,:,:,t);
if t<smpl
P = cat(3,P(:,:,1:t),repmat(P_s,[1 1 smpl-t]));
P1 = cat(3,P1(:,:,1:t),repmat(P1_s,[1 1 smpl-t]));
Fi = cat(2,Fi(:,1:t),repmat(Fi_s,[1 1 smpl-t]));
Li = cat(4,Li(:,:,:,1:t),repmat(L_s,[1 1 smpl-t]));
Ki = cat(3,Ki(:,:,1:t),repmat(Ki_s,[1 1 smpl-t]));
end
while t<smpl
t=t+1;
a(:,t) = a1(:,t);
di = data_index{t}';
for i=di
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);
end
end
a1(:,t+1) = T*a(:,t);
Pf = P(:,:,t);
for jnk=1:nk,
Pf = T*Pf*T' + QQ;
aK(jnk,:,t+jnk) = T^jnk*a(:,t);
PK(jnk,:,:,t+jnk) = Pf;
end
% notsteady = ~(max(max(abs(P(:,:,t+1)-P(:,:,t))))<crit);
end
% $$$ P_s=tril(P(:,:,t))+tril(P(:,:,t),-1)';
% $$$ P1_s=tril(P1(:,:,t))+tril(P1(:,:,t),-1)';
% $$$ Fi_s = Fi(:,t);
% $$$ Ki_s = Ki(:,:,t);
% $$$ L_s =Li(:,:,:,t);
% $$$ if t<smpl
% $$$ P = cat(3,P(:,:,1:t),repmat(P_s,[1 1 smpl-t]));
% $$$ P1 = cat(3,P1(:,:,1:t),repmat(P1_s,[1 1 smpl-t]));
% $$$ Fi = cat(2,Fi(:,1:t),repmat(Fi_s,[1 1 smpl-t]));
% $$$ Li = cat(4,Li(:,:,:,1:t),repmat(L_s,[1 1 smpl-t]));
% $$$ Ki = cat(3,Ki(:,:,1:t),repmat(Ki_s,[1 1 smpl-t]));
% $$$ end
% $$$ while t<smpl
% $$$ t=t+1;
% $$$ a(:,t) = a1(:,t);
% $$$ di = data_index{t}';
% $$$ for i=di
% $$$ Zi = Z(i,:);
% $$$ v(i,t) = Y(i,t) - Zi*a(:,t);
% $$$ if Fi_s(i) > crit
% $$$ a(:,t) = a(:,t) + Ki_s(:,i)*v(i,t)/Fi_s(i);
% $$$ end
% $$$ end
% $$$ a1(:,t+1) = T*a(:,t);
% $$$ Pf = P(:,:,t);
% $$$ for jnk=1:nk,
% $$$ Pf = T*Pf*T' + QQ;
% $$$ aK(jnk,:,t+jnk) = T^jnk*a(:,t);
% $$$ PK(jnk,:,:,t+jnk) = Pf;
% $$$ end
% $$$ end
ri=zeros(mm,1);
t = smpl+1;
while t > d+1