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corecting logic for selecting univariate diffuse filter and dealing 

with correlated measurement errors
time-shift
Michel Juillard 2012-01-22 18:37:29 +01:00
parent f0d1f033b0
commit cfb5114d41
2 changed files with 62 additions and 54 deletions
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22
matlab/dsge_likelihood.m
View File

@ -358,6 +358,7 @@ end
diffuse_periods = 0;
correlated_errors_have_been_checked = 0;
switch DynareOptions.lik_init
case 1% Standard initialization with the steady state of the state equation.
if kalman_algo~=2
@ -378,10 +379,14 @@ switch DynareOptions.lik_init
a = zeros(mm,1);
Zflag = 0;
case 3% Diffuse Kalman filter (Durbin and Koopman)
if kalman_algo ~= 4
% Use standard kalman filter except if the univariate filter is explicitely choosen.
if kalman_algo == 0
kalman_algo = 3;
elseif ~((kalman_algo == 3) || (kalman_algo == 4))
error(['diffuse filter: options_.kalman_algo can only be equal ' ...
'to 0 (default), 3 or 4'])
end
[Z,T,R,QT,Pstar,Pinf] = schur_statespace_transformation(Z,T,R,Q,DynareOptions.qz_criterium);
Zflag = 1;
% Run diffuse kalman filter on first periods.
@ -403,12 +408,10 @@ switch DynareOptions.lik_init
if isinf(dLIK)
% Go to univariate diffuse filter if singularity problem.
kalman_algo = 4;
singularity_flag = 1;
end
end
if (kalman_algo==4)
% Univariate Diffuse Kalman Filter
if singularity_flag
if isequal(H,0)
H = zeros(nobs,1);
mmm = mm;
@ -428,9 +431,11 @@ switch DynareOptions.lik_init
end
end
% no need to test again for correlation elements
singularity_flag = 0;
end
[dLIK,tmp,a,Pstar] = univariate_kalman_filter_d(DynareDataset.missing.aindex,DynareDataset.missing.number_of_observations,DynareDataset.missing.no_more_missing_observations, ...
correlated_errors_have_been_checked = 1;
[dLIK,tmp,a,Pstar] = univariate_kalman_filter_d(DynareDataset.missing.aindex,...
DynareDataset.missing.number_of_observations,...
DynareDataset.missing.no_more_missing_observations, ...
Y, 1, size(Y,2), ...
zeros(mmm,1), Pinf, Pstar, ...
kalman_tol, riccati_tol, DynareOptions.presample, ...
@ -605,7 +610,6 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
else
kalman_algo = 4;
end
singularity_flag = 1;
else
if DynareOptions.lik_init==3
LIK = LIK + dLIK;
@ -613,10 +617,10 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
end
end
if ( singularity_flag || (kalman_algo==2) || (kalman_algo==4) )
if (kalman_algo==2) || (kalman_algo==4)
% Univariate Kalman Filter
% resetting measurement error covariance matrix when necessary %
if singularity_flag
if ~correlated_errors_have_been_checked
if isequal(H,0)
H = zeros(nobs,1);
mmm = mm;

16
matlab/dsge_likelihood_hh.m
View File

@ -254,6 +254,7 @@ end
diffuse_periods = 0;
correlated_errors_have_been_checked = 0;
switch DynareOptions.lik_init
case 1% Standard initialization with the steady state of the state equation.
if kalman_algo~=2
@ -274,10 +275,14 @@ switch DynareOptions.lik_init
a = zeros(mm,1);
Zflag = 0;
case 3% Diffuse Kalman filter (Durbin and Koopman)
if kalman_algo ~= 4
% Use standard kalman filter except if the univariate filter is explicitely choosen.
if kalman_algo == 0
kalman_algo = 3;
elseif ~((kalman_algo == 3) || (kalman_algo == 4))
error(['diffuse filter: options_.kalman_algo can only be equal ' ...
'to 0 (default), 3 or 4'])
end
[Z,T,R,QT,Pstar,Pinf] = schur_statespace_transformation(Z,T,R,Q,DynareOptions.qz_criterium);
Zflag = 1;
% Run diffuse kalman filter on first periods.
@ -304,7 +309,6 @@ switch DynareOptions.lik_init
end
if (kalman_algo==4)
% Univariate Diffuse Kalman Filter
if singularity_flag
if isequal(H,0)
H = zeros(nobs,1);
mmm = mm;
@ -324,8 +328,8 @@ switch DynareOptions.lik_init
end
end
% no need to test again for correlation elements
singularity_flag = 0;
end
correlated_errors_have_been_checked = 1;
[dLIK,dlik,a,Pstar] = univariate_kalman_filter_d(DynareDataset.missing.aindex,DynareDataset.missing.number_of_observations,DynareDataset.missing.no_more_missing_observations, ...
Y, 1, size(Y,2), ...
zeros(mmm,1), Pinf, Pstar, ...
@ -385,10 +389,10 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
end
end
if ( singularity_flag || (kalman_algo==2) || (kalman_algo==4) )
if (kalman_algo==2) || (kalman_algo==4)
% Univariate Kalman Filter
% resetting measurement error covariance matrix when necessary %
if singularity_flag
if ~correlated_errors_have_been_checked
if isequal(H,0)
H = zeros(nobs,1);
mmm = mm;