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kalman_update_algo_1.m: introduce error handling 

Closes https://git.dynare.org/Dynare/dynare/-/issues/1854
mr#2067
Johannes Pfeifer 2022-05-19 11:56:42 +02:00
parent 05ab494d6c
commit 0f333f29eb
1 changed files with 40 additions and 6 deletions
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46
matlab/+occbin/kalman_update_algo_1.m
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@ -1,5 +1,5 @@
function [a, a1, P, P1, v, T, R, C, regimes_, error_flag, M_, lik, etahat] = kalman_update_algo_1(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,T0,R0,TT,RR,CC,regimes0,M_,oo_,options_,occbin_options)
% function [a, a1, P, P1, v, T, R, C, regimes_, info, M_, lik, etahat] = kalman_update_algo_1(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,T0,R0,TT,RR,CC,regimes0,M_,oo_,options_,occbin_options)
% function [a, a1, P, P1, v, T, R, C, regimes_, error_flag, M_, lik, etahat] = kalman_update_algo_1(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,T0,R0,TT,RR,CC,regimes0,M_,oo_,options_,occbin_options)
% INPUTS
% - a [N by 1] t-1's state estimate
% - a1 [N by 2] state predictions made at t-1:t
@ -61,6 +61,12 @@ function [a, a1, P, P1, v, T, R, C, regimes_, error_flag, M_, lik, etahat] = kal
warning off
regimes_=[]; %make sure it is always set
R=[];
C=[];
lik=Inf;
etahat=[];
sto.a=a;
sto.a1=a1;
sto.P=P;
@ -94,17 +100,19 @@ PZI = P1(:,:,t)*ZZ'*iF(di,di,t);
L(:,:,t) = eye(mm)-PZI*ZZ;
if ~options_.occbin.filter.use_relaxation
[a, a1, P, P1, v, alphahat, etahat, lik] = occbin_kalman_update0(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,TT,RR,CC,iF,L,mm, options_.rescale_prediction_error_covariance, options_.occbin.likelihood.IF_likelihood);
[a, a1, P, P1, v, alphahat, etahat, lik, error_flag] = occbin_kalman_update0(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,TT,RR,CC,iF,L,mm, options_.rescale_prediction_error_covariance, options_.occbin.likelihood.IF_likelihood);
else
[~,~,~,~,~,~, TTx, RRx, CCx] ...
= occbin.dynare_resolve(M_,options_,oo_, base_regime,'reduced_state_space',T0,R0);
regimes0(1)=base_regime;
TT(:,:,2) = TTx(:,:,end);
RR(:,:,2) = RRx(:,:,end);
CC(:,2) = CCx(:,end);
[a, a1, P, P1, v, alphahat, etahat, lik] = occbin_kalman_update0(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,TT,RR,CC,iF,L,mm, options_.rescale_prediction_error_covariance, options_.occbin.likelihood.IF_likelihood);
regimes0(1)=base_regime;
[a, a1, P, P1, v, alphahat, etahat, lik, error_flag] = occbin_kalman_update0(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,TT,RR,CC,iF,L,mm, options_.rescale_prediction_error_covariance, options_.occbin.likelihood.IF_likelihood);
end
if error_flag
return;
end
%% run here the occbin simul
opts_simul = occbin_options.opts_simul;
@ -121,7 +129,12 @@ else
my_order_var = oo_.dr.order_var;
end
options_.occbin.simul=opts_simul;
options_.noprint=1;
[~, out, ss] = occbin.solver(M_,oo_,options_);
if out.error_flag
error_flag = out.error_flag;
return;
end
regimes_ = out.regime_history;
if M_.occbin.constraint_nbr==1
@ -205,6 +218,10 @@ if any(myregime) || ~isequal(regimes_(1),regimes0(1))
opts_simul.periods = max(opts_simul.periods,max(myregimestart));
options_.occbin.simul=opts_simul;
[~, out, ss] = occbin.solver(M_,oo_,options_);
if out.error_flag
error_flag = out.error_flag;
return;
end
regimes0=regimes_;
regimes_ = out.regime_history;
if niter>1
@ -250,6 +267,10 @@ if any(myregime) || ~isequal(regimes_(1),regimes0(1))
opts_simul.maxit=1;
options_.occbin.simul=opts_simul;
[~, out, ss] = occbin.solver(M_,oo_,options_);
if out.error_flag
error_flag = out.error_flag;
return;
end
end
end
end
@ -303,6 +324,10 @@ if ~error_flag && niter>options_.occbin.likelihood.max_number_of_iterations && ~
opts_simul.periods = max(opts_simul.periods,max(myregimestart));
options_.occbin.simul=opts_simul;
[~, out, ss] = occbin.solver(M_,oo_,options_);
if out.error_flag
error_flag = out.error_flag;
return;
end
if isequal(out.regime_history(1),regimes_(1))
error_flag=0;
break
@ -326,7 +351,12 @@ etahat=etahat(:,2);
warning_config;
end
function [a, a1, P, P1, v, alphahat, etahat, lik] = occbin_kalman_update0(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,TT,RR,CC,iF,L,mm, rescale_prediction_error_covariance, IF_likelihood)
function [a, a1, P, P1, v, alphahat, etahat, lik, error_flag] = occbin_kalman_update0(a,a1,P,P1,data_index,Z,v,Y,H,QQQ,TT,RR,CC,iF,L,mm, rescale_prediction_error_covariance, IF_likelihood)
alphahat=[];
etahat=[];
lik=Inf;
error_flag=0;
warning off
if nargin<18
IF_likelihood=0;
@ -354,6 +384,10 @@ else
v(di,t) = Y(di,t) - ZZ*a(:,t);
F = ZZ*P(:,:,t)*ZZ' + H(di,di);
sig=sqrt(diag(F));
if any(any(isnan(F)))
error_flag=1;
return;
end
if rank(F)<size(F,1)
% here we trap cases when some OBC regime triggers singularity
% e.g. no shock to interest rate at ZLB