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Merge branch 'master' into remove-dynDate-class

issue#70
Stéphane Adjemian (Scylla) 2013-11-06 12:43:06 +01:00
parent d56393da98 6d6701aa50
commit aa4753f9ec
13 changed files with 123 additions and 50 deletions
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6
ComputingTasks.cc
View File

@ -2411,6 +2411,12 @@ CalibSmootherStatement::CalibSmootherStatement(const SymbolList &symbol_list_arg
{
}
void
CalibSmootherStatement::checkPass(ModFileStructure &mod_file_struct, WarningConsolidation &warnings)
{
mod_file_struct.calib_smoother_present = true;
}
void
CalibSmootherStatement::writeOutput(ostream &output, const string &basename) const
{

1
ComputingTasks.hh
View File

@ -516,6 +516,7 @@ private:
public:
CalibSmootherStatement(const SymbolList &symbol_list_arg,
const OptionsList &options_list_arg);
virtual void checkPass(ModFileStructure &mod_file_struct, WarningConsolidation &warnings);
virtual void writeOutput(ostream &output, const string &basename) const;
};

64
DynamicModel.cc
View File

@ -2913,26 +2913,23 @@ DynamicModel::writeOutput(ostream &output, const string &basename, bool block_de
output << "M_.exo_names_orig_ord = [1:" << symbol_table.exo_nbr() << "];" << endl
<< "M_.maximum_lag = " << max_lag << ";" << endl
<< "M_.maximum_lead = " << max_lead << ";" << endl;
if (symbol_table.endo_nbr())
{
output << "M_.maximum_endo_lag = " << max_endo_lag << ";" << endl
<< "M_.maximum_endo_lead = " << max_endo_lead << ";" << endl
<< "oo_.steady_state = zeros(" << symbol_table.endo_nbr() << ", 1);" << endl;
}
if (symbol_table.exo_nbr())
{
output << "M_.maximum_exo_lag = " << max_exo_lag << ";" << endl
<< "M_.maximum_exo_lead = " << max_exo_lead << ";" << endl
<< "oo_.exo_steady_state = zeros(" << symbol_table.exo_nbr() << ", 1);" << endl;
}
output << "M_.maximum_endo_lag = " << max_endo_lag << ";" << endl
<< "M_.maximum_endo_lead = " << max_endo_lead << ";" << endl
<< "oo_.steady_state = zeros(" << symbol_table.endo_nbr() << ", 1);" << endl;
output << "M_.maximum_exo_lag = " << max_exo_lag << ";" << endl
<< "M_.maximum_exo_lead = " << max_exo_lead << ";" << endl
<< "oo_.exo_steady_state = zeros(" << symbol_table.exo_nbr() << ", 1);" << endl;
if (symbol_table.exo_det_nbr())
{
output << "M_.maximum_exo_det_lag = " << max_exo_det_lag << ";" << endl
<< "M_.maximum_exo_det_lead = " << max_exo_det_lead << ";" << endl
<< "oo_.exo_det_steady_state = zeros(" << symbol_table.exo_det_nbr() << ", 1);" << endl;
}
if (symbol_table.param_nbr())
output << "M_.params = NaN(" << symbol_table.param_nbr() << ", 1);" << endl;
output << "M_.params = NaN(" << symbol_table.param_nbr() << ", 1);" << endl;
// Write number of non-zero derivatives
// Use -1 if the derivatives have not been computed
@ -3757,22 +3754,28 @@ DynamicModel::testTrendDerivativesEqualToZero(const eval_context_t &eval_context
|| symbol_table.getType(it->first.first) == eLogTrend)
for (int eq = 0; eq < (int) equations.size(); eq++)
{
expr_t testeq = AddLog(AddMinus(equations[eq]->get_arg1(), // F: a = b -> ln(a - b)
equations[eq]->get_arg2()));
testeq = testeq->getDerivative(it->second); // d F / d Trend
for (deriv_id_table_t::const_iterator endogit = deriv_id_table.begin();
endogit != deriv_id_table.end(); endogit++)
if (symbol_table.getType(endogit->first.first) == eEndogenous)
{
double nearZero = testeq->getDerivative(endogit->second)->eval(eval_context); // eval d F / d Trend d Endog
if (fabs(nearZero) > ZERO_BAND)
expr_t homogeneq = AddMinus(equations[eq]->get_arg1(),
equations[eq]->get_arg2());
// Do not run the test if the term inside the log is zero
if (fabs(homogeneq->eval(eval_context)) > ZERO_BAND)
{
expr_t testeq = AddLog(homogeneq); // F = log(lhs-rhs)
testeq = testeq->getDerivative(it->second); // d F / d Trend
for (deriv_id_table_t::const_iterator endogit = deriv_id_table.begin();
endogit != deriv_id_table.end(); endogit++)
if (symbol_table.getType(endogit->first.first) == eEndogenous)
{
cerr << "ERROR: trends not compatible with balanced growth path; the second-order cross partial of equation " << eq + 1 << " w.r.t. trend variable "
<< symbol_table.getName(it->first.first) << " and endogenous variable "
<< symbol_table.getName(endogit->first.first) << " is not null. " << endl;
exit(EXIT_FAILURE);
double nearZero = testeq->getDerivative(endogit->second)->eval(eval_context); // eval d F / d Trend d Endog
if (fabs(nearZero) > ZERO_BAND)
{
cerr << "ERROR: trends not compatible with balanced growth path; the second-order cross partial of equation " << eq + 1 << " w.r.t. trend variable "
<< symbol_table.getName(it->first.first) << " and endogenous variable "
<< symbol_table.getName(endogit->first.first) << " is not null. " << endl;
exit(EXIT_FAILURE);
}
}
}
}
}
}
@ -4134,8 +4137,9 @@ DynamicModel::transformPredeterminedVariables()
void
DynamicModel::detrendEquations()
{
for (nonstationary_symbols_map_t::const_iterator it = nonstationary_symbols_map.begin();
it != nonstationary_symbols_map.end(); it++)
// We go backwards in the list of trend_vars, to deal correctly with I(2) processes
for (nonstationary_symbols_map_t::const_reverse_iterator it = nonstationary_symbols_map.rbegin();
it != nonstationary_symbols_map.rend(); ++it)
for (int i = 0; i < (int) equations.size(); i++)
{
BinaryOpNode *substeq = dynamic_cast<BinaryOpNode *>(equations[i]->detrend(it->first, it->second.first, it->second.second));

16
DynareBison.yy
View File

@ -101,7 +101,7 @@ class ParsingDriver;
%token FILENAME FILTER_STEP_AHEAD FILTERED_VARS FIRST_OBS LAST_OBS SET_TIME
%token <string_val> FLOAT_NUMBER
%token DEFAULT FIXED_POINT
%token FORECAST K_ORDER_SOLVER INSTRUMENTS PRIOR SHIFT MEAN STDEV VARIANCE MODE INTERVAL SHAPE DOMAINN
%token FORECAST K_ORDER_SOLVER INSTRUMENTS SHIFT MEAN STDEV VARIANCE MODE INTERVAL SHAPE DOMAINN
%token GAMMA_PDF GRAPH GRAPH_FORMAT CONDITIONAL_VARIANCE_DECOMPOSITION NOCHECK STD
%token HISTVAL HOMOTOPY_SETUP HOMOTOPY_MODE HOMOTOPY_STEPS HOMOTOPY_FORCE_CONTINUE HP_FILTER HP_NGRID HYBRID
%token IDENTIFICATION INF_CONSTANT INITVAL INITVAL_FILE BOUNDS JSCALE INIT
@ -113,7 +113,7 @@ class ParsingDriver;
%token LYAPUNOV_FIXED_POINT_TOL LYAPUNOV_DOUBLING_TOL LYAPUNOV_SQUARE_ROOT_SOLVER_TOL LOG_DEFLATOR LOG_TREND_VAR LOG_GROWTH_FACTOR MARKOWITZ MARGINAL_DENSITY MAX MAXIT
%token MFS MH_DROP MH_INIT_SCALE MH_JSCALE MH_MODE MH_NBLOCKS MH_REPLIC MH_RECOVER MIN MINIMAL_SOLVING_PERIODS
%token MODE_CHECK MODE_CHECK_NEIGHBOURHOOD_SIZE MODE_CHECK_SYMMETRIC_PLOTS MODE_CHECK_NUMBER_OF_POINTS MODE_COMPUTE MODE_FILE MODEL MODEL_COMPARISON MODEL_INFO MSHOCKS ABS SIGN
%token MODEL_DIAGNOSTICS MODIFIEDHARMONICMEAN MOMENTS_VARENDO DIFFUSE_FILTER SUB_DRAWS TAPER_STEPS GEWEKE_INTERVAL
%token MODEL_DIAGNOSTICS MODIFIEDHARMONICMEAN MOMENTS_VARENDO DIFFUSE_FILTER SUB_DRAWS TAPER_STEPS GEWEKE_INTERVAL MCMC_JUMPING_COVARIANCE
%token <string_val> NAME
%token NAN_CONSTANT NO_STATIC NOBS NOCONSTANT NODISPLAY NOCORR NODIAGNOSTIC NOFUNCTIONS
%token NOGRAPH NOMOMENTS NOPRINT NORMAL_PDF SAVE_DRAWS
@ -151,7 +151,7 @@ class ParsingDriver;
%token VLISTLOG VLISTPER
%token RESTRICTION RESTRICTION_FNAME CROSS_RESTRICTIONS NLAGS CONTEMP_REDUCED_FORM REAL_PSEUDO_FORECAST
%token DUMMY_OBS NSTATES INDXSCALESSTATES NO_BAYESIAN_PRIOR SPECIFICATION SIMS_ZHA
%token <string_val> ALPHA BETA ABAND NINV CMS NCMS CNUM GAMMA INV_GAMMA INV_GAMMA1 INV_GAMMA2 NORMAL UNIFORM EPS PDF FIG DR NONE
%token <string_val> ALPHA BETA ABAND NINV CMS NCMS CNUM GAMMA INV_GAMMA INV_GAMMA1 INV_GAMMA2 NORMAL UNIFORM EPS PDF FIG DR NONE PRIOR PRIOR_VARIANCE HESSIAN IDENTITY_MATRIX
%token GSIG2_LMDM Q_DIAG FLAT_PRIOR NCSK NSTD
%token INDXPARR INDXOVR INDXAP APBAND INDXIMF IMFBAND INDXFORE FOREBAND INDXGFOREHAT INDXGIMFHAT
%token INDXESTIMA INDXGDLS EQ_MS FILTER_COVARIANCE FILTER_DECOMPOSITION
@ -1554,6 +1554,7 @@ estimation_options : o_datafile
| o_qz_zero_threshold
| o_taper_steps
| o_geweke_interval
| o_mcmc_jumping_covariance
;
list_optim_option : QUOTED_STRING COMMA QUOTED_STRING
@ -2673,6 +2674,14 @@ o_discretionary_tol: DISCRETIONARY_TOL EQUAL non_negative_number { driver.option
o_analytic_derivation : ANALYTIC_DERIVATION { driver.option_num("analytic_derivation", "1"); }
o_endogenous_prior : ENDOGENOUS_PRIOR { driver.option_num("endogenous_prior", "1"); }
o_use_univariate_filters_if_singularity_is_detected : USE_UNIVARIATE_FILTERS_IF_SINGULARITY_IS_DETECTED EQUAL INT_NUMBER { driver.option_num("use_univariate_filters_if_singularity_is_detected", $3); }
o_mcmc_jumping_covariance : MCMC_JUMPING_COVARIANCE EQUAL HESSIAN
{ driver.option_str("MCMC_jumping_covariance", $3); } | MCMC_JUMPING_COVARIANCE EQUAL PRIOR_VARIANCE
{ driver.option_str("MCMC_jumping_covariance", $3); }
| MCMC_JUMPING_COVARIANCE EQUAL IDENTITY_MATRIX
{ driver.option_str("MCMC_jumping_covariance", $3); }
| MCMC_JUMPING_COVARIANCE EQUAL filename
{ driver.option_str("MCMC_jumping_covariance", $3); }
;
range : symbol ':' symbol
{
@ -2791,6 +2800,7 @@ symbol : NAME
| FIG
| NONE
| DR
| PRIOR
;
%%

18
DynareFlex.ll
View File

@ -196,7 +196,10 @@ string eofbuff;
<DYNARE_STATEMENT>subsamples {return token::SUBSAMPLES;}
<DYNARE_STATEMENT>options {return token::OPTIONS;}
<DYNARE_STATEMENT>prior {return token::PRIOR;}
<DYNARE_STATEMENT>prior {
yylval->string_val = new string(yytext);
return token::PRIOR;
}
<INITIAL>std {BEGIN DYNARE_STATEMENT; return token::STD;}
<INITIAL>corr {BEGIN DYNARE_STATEMENT; return token::CORR;}
@ -436,6 +439,19 @@ string eofbuff;
<DYNARE_STATEMENT>random_parameter_convergence_criterion {return token::RANDOM_PARAMETER_CONVERGENCE_CRITERION;}
<DYNARE_STATEMENT>tolf {return token::TOLF;}
<DYNARE_STATEMENT>instruments {return token::INSTRUMENTS;}
<DYNARE_STATEMENT>hessian {
yylval->string_val = new string(yytext);
return token::HESSIAN;
}
<DYNARE_STATEMENT>prior_variance {
yylval->string_val = new string(yytext);
return token::PRIOR_VARIANCE;
}
<DYNARE_STATEMENT>identity_matrix {
yylval->string_val = new string(yytext);
return token::IDENTITY_MATRIX;
}
<DYNARE_STATEMENT>mcmc_jumping_covariance {return token::MCMC_JUMPING_COVARIANCE;}
/* These four (var, varexo, varexo_det, parameters) are for change_type */
<DYNARE_STATEMENT>var { return token::VAR; }

10
ExprNode.cc
View File

@ -21,15 +21,11 @@
#include <iterator>
#include <algorithm>
// For select1st()
#ifdef __GNUC__
# include <ext/functional>
using namespace __gnu_cxx;
#endif
#include <cassert>
#include <cmath>
#include <boost/bind.hpp>
#include "ExprNode.hh"
#include "DataTree.hh"
#include "ModFile.hh"
@ -110,7 +106,7 @@ ExprNode::collectModelLocalVariables(set<int> &result) const
set<pair<int, int> > symb_ids;
collectVariables(eModelLocalVariable, symb_ids);
transform(symb_ids.begin(), symb_ids.end(), inserter(result, result.begin()),
select1st<pair<int, int> >());
boost::bind(&pair<int,int>::first,_1));
}
void

24
ModFile.cc
View File

@ -123,7 +123,8 @@ ModFile::checkPass()
|| mod_file_struct.estimation_present
|| mod_file_struct.osr_present
|| mod_file_struct.ramsey_policy_present
|| mod_file_struct.discretionary_policy_present;
|| mod_file_struct.discretionary_policy_present
|| mod_file_struct.calib_smoother_present;
// Allow empty model only when doing a standalone BVAR estimation
if (dynamic_model.equation_number() == 0
@ -318,7 +319,8 @@ ModFile::transformPass(bool nostrict)
|| mod_file_struct.estimation_present
|| mod_file_struct.osr_present
|| mod_file_struct.ramsey_policy_present
|| mod_file_struct.discretionary_policy_present)
|| mod_file_struct.discretionary_policy_present
|| mod_file_struct.calib_smoother_present)
{
// In stochastic models, create auxiliary vars for leads and lags greater than 2, on both endos and exos
dynamic_model.substituteEndoLeadGreaterThanTwo(false);
@ -423,7 +425,8 @@ ModFile::computingPass(bool no_tmp_terms)
{
if (mod_file_struct.stoch_simul_present
|| mod_file_struct.estimation_present || mod_file_struct.osr_present
|| mod_file_struct.ramsey_policy_present || mod_file_struct.identification_present)
|| mod_file_struct.ramsey_policy_present || mod_file_struct.identification_present
|| mod_file_struct.calib_smoother_present)
static_model.set_cutoff_to_zero();
const bool static_hessian = mod_file_struct.identification_present
@ -437,7 +440,8 @@ ModFile::computingPass(bool no_tmp_terms)
if (mod_file_struct.simul_present || mod_file_struct.check_present
|| mod_file_struct.stoch_simul_present
|| mod_file_struct.estimation_present || mod_file_struct.osr_present
|| mod_file_struct.ramsey_policy_present || mod_file_struct.identification_present)
|| mod_file_struct.ramsey_policy_present || mod_file_struct.identification_present
|| mod_file_struct.calib_smoother_present)
{
if (mod_file_struct.simul_present)
dynamic_model.computingPass(true, false, false, false, global_eval_context, no_tmp_terms, block, use_dll, byte_code);
@ -445,7 +449,8 @@ ModFile::computingPass(bool no_tmp_terms)
{
if (mod_file_struct.stoch_simul_present
|| mod_file_struct.estimation_present || mod_file_struct.osr_present
|| mod_file_struct.ramsey_policy_present || mod_file_struct.identification_present)
|| mod_file_struct.ramsey_policy_present || mod_file_struct.identification_present
|| mod_file_struct.calib_smoother_present)
dynamic_model.set_cutoff_to_zero();
if (mod_file_struct.order_option < 1 || mod_file_struct.order_option > 3)
{
@ -532,15 +537,20 @@ ModFile::writeOutputFiles(const string &basename, bool clear_all, bool no_log, b
symbol_table.writeOutput(mOutputFile);
// Initialize M_.Sigma_e and M_.H
// Initialize M_.Sigma_e, M_.Correlation_matrix, M_.H, and M_.Correlation_matrix_ME
mOutputFile << "M_.Sigma_e = zeros(" << symbol_table.exo_nbr() << ", "
<< symbol_table.exo_nbr() << ");" << endl
<< "M_.Correlation_matrix = eye(" << symbol_table.exo_nbr() << ", "
<< symbol_table.exo_nbr() << ");" << endl;
if (mod_file_struct.calibrated_measurement_errors)
mOutputFile << "M_.H = zeros(" << symbol_table.observedVariablesNbr() << ", "
<< symbol_table.observedVariablesNbr() << ");" << endl
<< "M_.Correlation_matrix_ME = eye(" << symbol_table.observedVariablesNbr() << ", "
<< symbol_table.observedVariablesNbr() << ");" << endl;
else
mOutputFile << "M_.H = 0;" << endl;
mOutputFile << "M_.H = 0;" << endl
<< "M_.Correlation_matrix_ME = 1;" << endl;
if (linear == 1)
mOutputFile << "options_.linear = 1;" << endl;

7
ModelTree.cc
View File

@ -1567,3 +1567,10 @@ ModelTree::computeParamsDerivativesTemporaryTerms()
it != hessian_params_derivatives.end(); ++it)
it->second->computeTemporaryTerms(reference_count, params_derivs_temporary_terms, true);
}
bool ModelTree::isNonstationary(int symb_id) const
{
return (nonstationary_symbols_map.find(symb_id)
!= nonstationary_symbols_map.end());
}

2
ModelTree.hh
View File

@ -307,6 +307,8 @@ public:
void addTrendVariables(vector<int> trend_vars, expr_t growth_factor) throw (TrendException);
//! Adds a nonstationary variables with their (common) deflator
void addNonstationaryVariables(vector<int> nonstationary_vars, bool log_deflator, expr_t deflator) throw (TrendException);
//! Is a given variable non-stationary?
bool isNonstationary(int symb_id) const;
void set_cutoff_to_zero();
//! Helper for writing the Jacobian elements in MATLAB and C
/*! Writes either (i+1,j+1) or [i+j*no_eq] */

7
ParsingDriver.cc
View File

@ -357,6 +357,13 @@ ParsingDriver::end_nonstationary_var(bool log_deflator, expr_t deflator)
{
error("Variable " + e.name + " was listed more than once as following a trend.");
}
set<pair<int, int> > r;
deflator->collectVariables(eEndogenous, r);
for (set<pair<int, int> >::const_iterator it = r.begin(); it != r.end(); ++it)
if (dynamic_model->isNonstationary(it->first))
error("The deflator contains a non-stationary endogenous variable. This is not allowed. Please use only stationary endogenous and/or {log_}trend_vars.");
declared_nonstationary_vars.clear();
reset_data_tree();
}

13
Shocks.cc
View File

@ -155,17 +155,19 @@ ShocksStatement::writeCovarOrCorrShock(ostream &output, covar_and_corr_shocks_t:
SymbolType type2 = symbol_table.getType(it->first.second);
assert((type1 == eExogenous && type2 == eExogenous)
|| (symbol_table.isObservedVariable(it->first.first) && symbol_table.isObservedVariable(it->first.second)));
string matrix;
string matrix, corr_matrix;
int id1, id2;
if (type1 == eExogenous)
{
matrix = "M_.Sigma_e";
corr_matrix = "M_.Correlation_matrix";
id1 = symbol_table.getTypeSpecificID(it->first.first) + 1;
id2 = symbol_table.getTypeSpecificID(it->first.second) + 1;
}
else
{
matrix = "M_.H";
corr_matrix = "M_.Correlation_matrix_ME";
id1 = symbol_table.getObservedVariableIndex(it->first.first) + 1;
id2 = symbol_table.getObservedVariableIndex(it->first.second) + 1;
}
@ -178,6 +180,15 @@ ShocksStatement::writeCovarOrCorrShock(ostream &output, covar_and_corr_shocks_t:
output << ";" << endl
<< matrix << "(" << id2 << ", " << id1 << ") = "
<< matrix << "(" << id1 << ", " << id2 << ");" << endl;
if (corr)
{
output << corr_matrix << "(" << id1 << ", " << id2 << ") = ";
it->second->writeOutput(output);
output << ";" << endl
<< corr_matrix << "(" << id2 << ", " << id1 << ") = "
<< corr_matrix << "(" << id1 << ", " << id2 << ");" << endl;
}
}
void

3
Statement.cc
View File

@ -47,7 +47,8 @@ ModFileStructure::ModFileStructure() :
dsge_var_estimated(false),
bayesian_irf_present(false),
estimation_data_statement_present(false),
last_markov_switching_chain(0)
last_markov_switching_chain(0),
calib_smoother_present(false)
{
}

2
Statement.hh
View File

@ -97,6 +97,8 @@ public:
bool estimation_data_statement_present;
//! Last chain number for Markov Switching statement
int last_markov_switching_chain;
//! Whether a calib_smoother statement is present
bool calib_smoother_present;
};
class Statement