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Merge remote branch 'george/master'

time-shift
Sébastien Villemot 2010-04-16 18:34:57 +02:00
parent d72ca78d0b e9846ae65f
commit 18c36c3dd5
5 changed files with 10 additions and 24 deletions
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13
mex/sources/estimation/KalmanFilter.cc
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@ -39,9 +39,9 @@ KalmanFilter::KalmanFilter(const std::string &modName, size_t n_endo, size_t n_e
double riccati_tol_in, double lyapunov_tol, int &info) :
Z(varobs_arg.size(), riv.size()), T(riv.size()), R(riv.size(), n_exo),
Pstar(riv.size(), riv.size()), Pinf(riv.size(), riv.size()), RQRt(riv.size(), riv.size()),
Pold(riv.size(), riv.size()), Ptmp(riv.size(), riv.size()), F(varobs_arg.size(), varobs_arg.size()),
Finv(varobs_arg.size(), varobs_arg.size()), K(riv.size(), varobs_arg.size()),
KFinv(riv.size(), varobs_arg.size()), Finverter(varobs_arg.size()), a_init(riv.size(), 1),
Ptmp(riv.size(), riv.size()), F(varobs_arg.size(), varobs_arg.size()),
Finv(varobs_arg.size(), varobs_arg.size()), K(riv.size(), varobs_arg.size()), KFinv(riv.size(), varobs_arg.size()),
oldKFinv(riv.size(), varobs_arg.size()), Finverter(varobs_arg.size()), a_init(riv.size(), 1),
a_new(riv.size(), 1), vt(varobs_arg.size(), 1), vtFinv(1, varobs_arg.size()), vtFinvVt(1), riccati_tol(riccati_tol_in),
initKalmanFilter(modName, n_endo, n_exo, zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg,
zeta_static_arg, ll_incidence, qz_criterium, order_var, inv_order_var, riv, ric, lyapunov_tol, info)
@ -94,7 +94,7 @@ KalmanFilter::filter(const Matrix &dataView, const Matrix &H, Vector &vll, size
// Finv=inv(F)
mat::set_identity(Finv);
Finverter.invMult("N", F, Finv); // F now contains its LU decomposition!
// KFinv
// KFinv gain matrix
KFinv.setAll(0.0);
blas::gemm("N", "N", 1.0, K, Finv, 1.0, KFinv);
// deteminant of F:
@ -104,7 +104,6 @@ KalmanFilter::filter(const Matrix &dataView, const Matrix &H, Vector &vll, size
logFdet=log(fabs(Fdet));
Pold = Pstar;
Ptmp = Pstar;
// Pt+1= T(Pt - KFinvK')T' +RQR'
// 1) Ptmp= Pt - K*FinvK'
@ -116,7 +115,9 @@ KalmanFilter::filter(const Matrix &dataView, const Matrix &H, Vector &vll, size
// 3) Pt+1= Ptmp*T' +RQR'
Pstar = RQRt;
blas::gemm("N", "T", 1.0, Ptmp, T, 1.0, Pstar);
nonstationary = mat::isDiffSym(Pstar, Pold, riccati_tol);
if (t>0)
nonstationary = mat::isDiff(KFinv, oldKFinv, riccati_tol);
oldKFinv=KFinv;
}
// err= Yt - Za

4
mex/sources/estimation/KalmanFilter.hh
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@ -68,9 +68,9 @@ private:
Matrix Pstar; //mm*mm variance-covariance matrix of stationary variables
Matrix Pinf; //mm*mm variance-covariance matrix of diffuse variables
// allocate space for intermediary matrices
Matrix RQRt, Pold, Ptmp; //mm*mm variance-covariance matrix of variable disturbances
Matrix RQRt, Ptmp; //mm*mm variance-covariance matrix of variable disturbances
Matrix F, Finv; // nob*nob F=ZPZt +H an inv(F)
Matrix K, KFinv; // mm*nobs K=PZt and nm*nm K*Finv
Matrix K, KFinv, oldKFinv; // mm*nobs K=PZt and K*Finv gain matrices
LUSolver Finverter; // matrix inversion algorithm
Matrix a_init, a_new; // state vector
Matrix vt; // current observation error vectors

9
mex/sources/estimation/ModelSolution.cc
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@ -71,17 +71,10 @@ ModelSolution::ComputeModelSolution(Vector& steadyState, const Vector& deepParam
llXsteadyState(((size_t) ll_incidence(ll_row, i))-1) = steadyState(i);
}
}
#ifdef DEBUG
// std::cout << "Vector llXsteadyState: " << std::endl << llXsteadyState << std::endl;
mexPrintf(" get jacobian \n");
#endif
//get jacobian
dynamicDLLp.eval(llXsteadyState, Mx, &deepParams, 1, residual, &jacobian, NULL, NULL);
#ifdef DEBUG
std::cout << "jacobian: " << std::endl << jacobian << std::endl;
mexPrintf(" compute rules \n");
#endif
//compute rules
decisionRules.compute(jacobian,ghx, ghu);
}

4
mex/sources/estimation/tests/testInitKalman.cc
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@ -49,10 +49,6 @@ main(int argc, char **argv)
0.3167, 0.8610, 1.0085, 0.9917,
1.3559, 1.0085, 0.9929
};
double vcov1[] = {
0.1960e-3, 0.0,
0.0, 0.0250e-3
};
double vcov[] = {
0.0013, 0,

4
mex/sources/estimation/tests/testKalman.cc
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@ -49,10 +49,6 @@ main(int argc, char **argv)
0.3167, 0.8610, 1.0085, 0.9917,
1.3559, 1.0085, 0.9929
};
double vcov1[] = {
0.1960e-3, 0.0,
0.0, 0.0250e-3
};
double vcov[] = {
0.0013, 0,