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calling always multivariate Kalman filter first, even if univariate 

diffuse Kalman filter was used before
time-shift
Michel Juillard 2012-01-22 18:59:19 +01:00
parent cfb5114d41
commit 636cd1bae6
2 changed files with 20 additions and 17 deletions
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13
matlab/dsge_likelihood.m
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@ -359,6 +359,7 @@ end
diffuse_periods = 0; diffuse_periods = 0;
correlated_errors_have_been_checked = 0; correlated_errors_have_been_checked = 0;
singular_diffuse_filter = 0;
switch DynareOptions.lik_init switch DynareOptions.lik_init
case 1% Standard initialization with the steady state of the state equation. case 1% Standard initialization with the steady state of the state equation.
if kalman_algo~=2 if kalman_algo~=2
@ -407,17 +408,17 @@ switch DynareOptions.lik_init
diffuse_periods = length(tmp); diffuse_periods = length(tmp);
if isinf(dLIK) if isinf(dLIK)
% Go to univariate diffuse filter if singularity problem. % Go to univariate diffuse filter if singularity problem.
kalman_algo = 4; singular_diffuse_filter = 1;
end end
end end
if (kalman_algo==4) if singular_diffuse_filter || (kalman_algo==4)
% Univariate Diffuse Kalman Filter % Univariate Diffuse Kalman Filter
if isequal(H,0) if isequal(H,0)
H = zeros(nobs,1); H1 = zeros(nobs,1);
mmm = mm; mmm = mm;
else else
if all(all(abs(H-diag(diag(H)))<1e-14))% ie, the covariance matrix is diagonal... if all(all(abs(H-diag(diag(H)))<1e-14))% ie, the covariance matrix is diagonal...
H = diag(H); H1 = diag(H);
mmm = mm; mmm = mm;
else else
Z = [Z, eye(pp)]; Z = [Z, eye(pp)];
@ -426,7 +427,7 @@ switch DynareOptions.lik_init
R = blkdiag(R,eye(pp)); R = blkdiag(R,eye(pp));
Pstar = blkdiag(Pstar,H); Pstar = blkdiag(Pstar,H);
Pinf = blckdiag(Pinf,zeros(pp)); Pinf = blckdiag(Pinf,zeros(pp));
H = zeros(nobs,1); H1 = zeros(nobs,1);
mmm = mm+pp; mmm = mm+pp;
end end
end end
@ -439,7 +440,7 @@ switch DynareOptions.lik_init
Y, 1, size(Y,2), ... Y, 1, size(Y,2), ...
zeros(mmm,1), Pinf, Pstar, ... zeros(mmm,1), Pinf, Pstar, ...
kalman_tol, riccati_tol, DynareOptions.presample, ... kalman_tol, riccati_tol, DynareOptions.presample, ...
T,R,Q,H,Z,mmm,pp,rr); T,R,Q,H1,Z,mmm,pp,rr);
diffuse_periods = length(tmp); diffuse_periods = length(tmp);
end end
case 4% Start from the solution of the Riccati equation. case 4% Start from the solution of the Riccati equation.

24
matlab/dsge_likelihood_hh.m
View File

@ -255,6 +255,7 @@ end
diffuse_periods = 0; diffuse_periods = 0;
correlated_errors_have_been_checked = 0; correlated_errors_have_been_checked = 0;
singular_diffuse_filter = 0;
switch DynareOptions.lik_init switch DynareOptions.lik_init
case 1% Standard initialization with the steady state of the state equation. case 1% Standard initialization with the steady state of the state equation.
if kalman_algo~=2 if kalman_algo~=2
@ -303,18 +304,17 @@ switch DynareOptions.lik_init
diffuse_periods = length(dlik); diffuse_periods = length(dlik);
if isinf(dLIK) if isinf(dLIK)
% Go to univariate diffuse filter if singularity problem. % Go to univariate diffuse filter if singularity problem.
kalman_algo = 4; singular_diffuse_filter
singularity_flag = 1;
end end
end end
if (kalman_algo==4) if singular_diffuse_filter || (kalman_algo==4)
% Univariate Diffuse Kalman Filter % Univariate Diffuse Kalman Filter
if isequal(H,0) if isequal(H,0)
H = zeros(nobs,1); H1 = zeros(nobs,1);
mmm = mm; mmm = mm;
else else
if all(all(abs(H-diag(diag(H)))<1e-14))% ie, the covariance matrix is diagonal... if all(all(abs(H-diag(diag(H)))<1e-14))% ie, the covariance matrix is diagonal...
H = diag(H); H1 = diag(H);
mmm = mm; mmm = mm;
else else
Z = [Z, eye(pp)]; Z = [Z, eye(pp)];
@ -323,18 +323,20 @@ switch DynareOptions.lik_init
R = blkdiag(R,eye(pp)); R = blkdiag(R,eye(pp));
Pstar = blkdiag(Pstar,H); Pstar = blkdiag(Pstar,H);
Pinf = blckdiag(Pinf,zeros(pp)); Pinf = blckdiag(Pinf,zeros(pp));
H = zeros(nobs,1); H1 = zeros(nobs,1);
mmm = mm+pp; mmm = mm+pp;
end end
end end
% no need to test again for correlation elements % no need to test again for correlation elements
correlated_errors_have_been_checked = 1; 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, ... [dLIK,dlik,a,Pstar] = univariate_kalman_filter_d(DynareDataset.missing.aindex,...
Y, 1, size(Y,2), ... DynareDataset.missing.number_of_observations,...
zeros(mmm,1), Pinf, Pstar, ... DynareDataset.missing.no_more_missing_observations, ...
kalman_tol, riccati_tol, DynareOptions.presample, ... Y, 1, size(Y,2), ...
T,R,Q,H,Z,mmm,pp,rr); zeros(mmm,1), Pinf, Pstar, ...
kalman_tol, riccati_tol, DynareOptions.presample, ...
T,R,Q,H1,Z,mmm,pp,rr);
diffuse_periods = length(dlik); diffuse_periods = length(dlik);
end end
case 4% Start from the solution of the Riccati equation. case 4% Start from the solution of the Riccati equation.