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Commit 3d1a0c26 authored by Ferhat Mihoubi's avatar Ferhat Mihoubi
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block-Kalman filter is now available when block option is used

parent 6e340c2c
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matlab/DsgeLikelihood.m
View file @ 3d1a0c26
......@@ -278,7 +278,11 @@ end
%------------------------------------------------------------------------------
if (kalman_algo==1)% Multivariate Kalman Filter
if no_missing_data_flag
LIK = kalman_filter(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol);
if options_.block == 1
LIK = block_kalman_filter(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol, M_.nz_state_var, M_.n_diag);
else
LIK = kalman_filter(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol);
end;
if analytic_derivation,
if no_DLIK==0,
[DLIK] = score(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,mf,kalman_tol,riccati_tol);
......
mex/sources/block_kalman_filter/block_kalman_filter.cc 0 → 100644
View file @ 3d1a0c26
This diff is collapsed.
preprocessor/DynamicModel.cc
View file @ 3d1a0c26
......@@ -2253,7 +2253,7 @@ DynamicModel::writeDynamicModel(ostream &DynamicOutput, bool use_dll) const
}
void
DynamicModel::writeOutput(ostream &output, const string &basename, bool block_decomposition, bool byte_code, bool use_dll, int order) const
DynamicModel::writeOutput(ostream &output, const string &basename, bool block_decomposition, bool byte_code, bool use_dll, int order, bool estimation_present) const
{
/* Writing initialisation for M_.lead_lag_incidence matrix
M_.lead_lag_incidence is a matrix with as many columns as there are
......@@ -2264,7 +2264,7 @@ DynamicModel::writeOutput(ostream &output, const string &basename, bool block_de
model at a given period.
*/
vector<int> state_var;
vector<int> state_var, state_equ;
output << "M_.lead_lag_incidence = [";
// Loop on endogenous variables
int nstatic = 0,
......@@ -2558,6 +2558,14 @@ DynamicModel::writeOutput(ostream &output, const string &basename, bool block_de
for (int i = 0; i < nb_endo; i++)
output << " " << equation_reordered[i]+1;
output << "];\n";
vector<int> variable_inv_reordered(nb_endo);
for (int i = 0; i< nb_endo; i++)
variable_inv_reordered[variable_reordered[i]] = i;
for (vector<int>::const_iterator it=state_var.begin(); it != state_var.end(); it++)
state_equ.push_back(equation_reordered[variable_inv_reordered[*it - 1]]+1);
map<pair< int, pair<int, int> >, int> lag_row_incidence;
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
......@@ -2586,6 +2594,235 @@ DynamicModel::writeOutput(ostream &output, const string &basename, bool block_de
output << it->first.second.first+1 << " " << it->first.second.second+1 << ";\n";
}
output << "];\n";
if (estimation_present)
{
ofstream KF_index_file;
string main_name = basename;
main_name += ".kfi";
KF_index_file.open(main_name.c_str(), ios::out | ios::binary | ios::ate);
int n_obs = symbol_table.observedVariablesNbr();
int n_state = state_var.size();
int n = n_obs + n_state;
int nb_diag = 0;
//map<pair<int,int>, int>::const_iterator row_state_var_incidence_it = row_state_var_incidence.begin();
vector<int> i_nz_state_var(n);
unsigned int lp = symbol_table.observedVariablesNbr();
for (int i = 0; i < n_obs; i++)
i_nz_state_var[i] = n;
for (int block = 0; block < nb_blocks; block++)
{
int block_size = getBlockSize(block);
int nze = 0;
for (int i = 0; i < block_size; i++)
{
int var = getBlockVariableID(block, i);
vector<int>::const_iterator it_state_var = find(state_var.begin(), state_var.end(), var+1);
if (it_state_var != state_var.end())
nze++;
}
if (block == 0)
{
set<pair<int, int> > row_state_var_incidence;
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
vector<int>::const_iterator it_state_var = find(state_var.begin(), state_var.end(), getBlockVariableID(block, it->first.second)+1);
if (it_state_var != state_var.end())
{
vector<int>::const_iterator it_state_equ = find(state_equ.begin(), state_equ.end(), getBlockEquationID(block, it->first.first)+1);
if (it_state_equ != state_equ.end())
row_state_var_incidence.insert(make_pair(it_state_equ - state_equ.begin(), it_state_var - state_var.begin()));
}
}
/*tmp_block_endo_derivative[make_pair(it->second.first, make_pair(it->first.second, it->first.first))] = it->second.second;
if (block == 0)
{
vector<int>::const_iterator it_state_equ = find(state_equ.begin(), state_equ.end(), getBlockEquationID(block, i)+1);
if (it_state_equ != state_equ.end())
{
cout << "row_state_var_incidence[make_pair([" << *it_state_equ << "] " << it_state_equ - state_equ.begin() << ", [" << *it_state_var << "] " << it_state_var - state_var.begin() << ")] = 1;\n";
row_state_var_incidence.insert(make_pair(it_state_equ - state_equ.begin(), it_state_var - state_var.begin()));
}
}*/
set<pair<int,int> >::const_iterator row_state_var_incidence_it = row_state_var_incidence.begin();
bool diag = true;
int nb_diag_r = 0;
while (row_state_var_incidence_it != row_state_var_incidence.end() && diag)
{
diag = (row_state_var_incidence_it->first == row_state_var_incidence_it->second);
if (diag)
{
int equ = row_state_var_incidence_it->first;
row_state_var_incidence_it++;
if (equ != row_state_var_incidence_it->first)
nb_diag_r++;
}
}
set<pair<int,int> > col_state_var_incidence;
for(set<pair<int,int> >::const_iterator row_state_var_incidence_it = row_state_var_incidence.begin();row_state_var_incidence_it != row_state_var_incidence.end(); row_state_var_incidence_it++)
col_state_var_incidence.insert(make_pair(row_state_var_incidence_it->second, row_state_var_incidence_it->first));
set<pair<int,int> >::const_iterator col_state_var_incidence_it = col_state_var_incidence.begin();
diag = true;
int nb_diag_c = 0;
while (col_state_var_incidence_it != col_state_var_incidence.end() && diag)
{
diag = (col_state_var_incidence_it->first == col_state_var_incidence_it->second);
if (diag)
{
int var = col_state_var_incidence_it->first;
col_state_var_incidence_it++;
if (var != col_state_var_incidence_it->first)
nb_diag_c++;
}
}
nb_diag = min( nb_diag_r, nb_diag_c);
row_state_var_incidence.clear();
col_state_var_incidence.clear();
}
for (int i = 0; i < nze; i++)
i_nz_state_var[lp + i] = lp + nze;
lp += nze;
}
output << "M_.nz_state_var = [";
for (int i = 0; i < lp; i++)
output << i_nz_state_var[i] << " ";
output << "];" << endl;
output << "M_.n_diag = " << nb_diag << ";" << endl;
KF_index_file.write(reinterpret_cast<char *>(&nb_diag), sizeof(nb_diag));
typedef pair<int, pair<int, int > > index_KF;
vector<index_KF> v_index_KF;
/* DO 170, J = 1, N
TEMP1 = ALPHA*A( J, J )
DO 110, I = 1, M
C( I, J ) = TEMP1*B( I, J )
11 110 CONTINUE
DO 140, K = 1, J - 1
TEMP1 = ALPHA*A( K, J )
DO 130, I = 1, M
C( I, J ) = C( I, J ) + TEMP1*B( I, K )
13 130 CONTINUE
14 140 CONTINUE
DO 160, K = J + 1, N
TEMP1 = ALPHA*A( J, K )
DO 150, I = 1, M
C( I, J ) = C( I, J ) + TEMP1*B( I, K )
15 150 CONTINUE
16 160 CONTINUE
17 170 CONTINUE
for(int j = 0; j < n; j++)
{
double temp1 = P_t_t1[j + j * n];
for (int i = 0; i < n; i++)
tmp[i + j * n] = tmp1 * T[i + j * n];
for (int k = 0; k < j - 1; k++)
{
temp1 = P_t_t1[k + j * n];
for (int i = 0; i < n; i++)
tmp[i + j * n] += temp1 * T[i + k * n];
}
for (int k = j + 1; k < n; k++)
{
temp1 = P_t_t1[j + k * n];
for (int i = 0; i < n; i++)
tmp[i + j * n] += temp1 * T[i + k * n];
}
}
for(int j = n_obs; j < n; j++)
{
int j1 = j - n_obs;
double temp1 = P_t_t1[j1 + j1 * n_state];
for (int i = 0; i < n; i++)
tmp[i + j1 * n] = tmp1 * T[i + j * n];
for (int k = n_obs; k < j - 1; k++)
{
int k1 = k - n_obs;
temp1 = P_t_t1[k1 + j1 * n_state];
for (int i = 0; i < n; i++)
tmp[i + j1 * n] += temp1 * T[i + k * n];
}
for (int k = max(j + 1, n_obs); k < n; k++)
{
int k1 = k - n_obs;
temp1 = P_t_t1[j1 + k1 * n_state];
for (int i = 0; i < n; i++)
tmp[i + j1 * n] += temp1 * T[i + k * n];
}
}
for(int j = n_obs; j < n; j++)
{
int j1 = j - n_obs;
double temp1 = P_t_t1[j1 + j1 * n_state];
for (int i = 0; i < n; i++)
tmp[i + j1 * n] = tmp1 * T[i + j * n];
for (int k = n_obs; k < j - 1; k++)
{
int k1 = k - n_obs;
temp1 = P_t_t1[k1 + j1 * n_state];
for (int i = 0; i < n; i++)
if ((i < n_obs) || (i >= nb_diag + n_obs) || (j1 >= nb_diag))
tmp[i + j1 * n] += temp1 * T[i + k * n];
}
for (int k = max(j + 1, n_obs); k < n; k++)
{
int k1 = k - n_obs;
temp1 = P_t_t1[j1 + k1 * n_state];
for (int i = 0; i < n; i++)
if ((i < n_obs) || (i >= nb_diag + n_obs) || (j1 >= nb_diag))
tmp[i + j1 * n] += temp1 * T[i + k * n];
}
}*/
for (int i = 0; i < n; i++)
//int i = 0;
for (int j = n_obs; j < n; j++)
{
int j1 = j - n_obs;
int j1_n_state = j1 * n_state - n_obs ;
if ((i < n_obs) || (i >= nb_diag + n_obs) || (j1 >= nb_diag))
for (int k = n_obs; k < i_nz_state_var[i]; k++)
{
v_index_KF.push_back(make_pair(i + j1 * n, make_pair(i + k * n, k + j1_n_state)));
}
}
int size_v_index_KF = v_index_KF.size();
cout << "size_v_index_KF=" << size_v_index_KF << endl;
KF_index_file.write(reinterpret_cast<char *>(&size_v_index_KF), sizeof(size_v_index_KF));
for (vector<index_KF>::iterator it = v_index_KF.begin(); it != v_index_KF.end(); it++)
KF_index_file.write(reinterpret_cast<char *>(&(*it)), sizeof(index_KF));
//typedef pair<pair<int, int>, pair<int, int > > index_KF_2;
vector<index_KF> v_index_KF_2;
int n_n_obs = n * n_obs;
for (int i = 0; i < n; i++)
//i = 0;
for (int j = i; j < n; j++)
{
if ((i < n_obs) || (i >= nb_diag + n_obs) || (j < n_obs) || (j >= nb_diag + n_obs))
for (int k = n_obs; k < i_nz_state_var[j]; k++)
{
int k_n = k * n;
v_index_KF_2.push_back(make_pair(i * n + j, make_pair(i + k_n - n_n_obs, j + k_n)));
}
}
int size_v_index_KF_2 = v_index_KF_2.size();
cout << "size_v_index_KF_2=" << size_v_index_KF_2 << endl;
KF_index_file.write(reinterpret_cast<char *>(&size_v_index_KF_2), sizeof(size_v_index_KF_2));
for (vector<index_KF>::iterator it = v_index_KF_2.begin(); it != v_index_KF_2.end(); it++)
KF_index_file.write(reinterpret_cast<char *>(&(*it)), sizeof(index_KF));
KF_index_file.close();
/*ofstream KF_index_file;
streamoff Code_Size;
KF_index_file.open((file_name + ".kfi").c_str(), std::ios::in | std::ios::binary| std::ios::ate);*/
}
}
// Writing initialization for some other variables
output << "M_.state_var = [";
......
preprocessor/DynamicModel.hh
View file @ 3d1a0c26
......@@ -245,7 +245,7 @@ public:
void computingPass(bool jacobianExo, bool hessian, bool thirdDerivatives, bool paramsDerivatives,
const eval_context_t &eval_context, bool no_tmp_terms, bool block, bool use_dll, bool bytecode);
//! Writes model initialization and lead/lag incidence matrix to output
void writeOutput(ostream &output, const string &basename, bool block, bool byte_code, bool use_dll, int order) const;
void writeOutput(ostream &output, const string &basename, bool block, bool byte_code, bool use_dll, int order, bool estimation_present) const;
//! Adds informations for simulation in a binary file
void Write_Inf_To_Bin_File_Block(const string &dynamic_basename, const string &bin_basename,
......
preprocessor/ModFile.cc
View file @ 3d1a0c26
......@@ -568,7 +568,7 @@ ModFile::writeOutputFiles(const string &basename, bool clear_all, bool console,
if (dynamic_model.equation_number() > 0)
{
dynamic_model.writeOutput(mOutputFile, basename, block, byte_code, use_dll, mod_file_struct.order_option);
dynamic_model.writeOutput(mOutputFile, basename, block, byte_code, use_dll, mod_file_struct.order_option, mod_file_struct.estimation_present);
if (!no_static)
static_model.writeOutput(mOutputFile, block);
}
......
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