110 lines
3.8 KiB
C++
110 lines
3.8 KiB
C++
/*
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* Copyright (C) 2010-2017 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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///////////////////////////////////////////////////////////
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// InitializeKalmanFilter.h
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// Implementation of the Class InitializeKalmanFilter
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// Created on: 02-Feb-2010 12:25:28
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///////////////////////////////////////////////////////////
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#if !defined(C3D996B8_22AB_4b77_B693_BA4777AFB091__INCLUDED_)
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#define C3D996B8_22AB_4b77_B693_BA4777AFB091__INCLUDED_
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#include "DetrendData.hh"
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#include "ModelSolution.hh"
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#include "DiscLyapFast.hh"
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#include <string>
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/**
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* if model is declared stationary ?compute covariance matrix of endogenous
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* variables () by doubling algorithm
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*
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*/
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class InitializeKalmanFilter
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{
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public:
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/*!
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\param[in] zeta_varobs_back_mixed_arg The union of indices of observed, backward and mixed variables
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*/
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InitializeKalmanFilter(const std::string &basename, size_t n_endo, size_t n_exo, const std::vector<size_t> &zeta_fwrd_arg,
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const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg,
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const std::vector<size_t> &zeta_varobs_back_mixed_arg,
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const std::vector<size_t> &varobs_arg,
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double qz_criterium_arg, double lyapunov_tol_arg,
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bool noconstant_arg);
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virtual
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~InitializeKalmanFilter();
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// initialise parameter dependent KF matrices only but not Ps
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template <class Vec1, class Vec2, class Mat1, class Mat2>
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void
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initialize(Vec1 &steadyState, const Vec2 &deepParams, Mat1 &R,
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const Mat2 &Q, Matrix &RQRt, Matrix &T,
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const MatrixConstView &dataView,
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MatrixView &detrendedDataView)
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{
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modelSolution.compute(steadyState, deepParams, g_x, g_u);
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detrendData.detrend(steadyState, dataView, detrendedDataView);
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setT(T);
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setRQR(R, Q, RQRt);
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}
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// initialise all KF matrices
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template <class Vec1, class Vec2, class Mat1, class Mat2>
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void
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initialize(Vec1 &steadyState, const Vec2 &deepParams, Mat1 &R,
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const Mat2 &Q, Matrix &RQRt, Matrix &T, Matrix &Pstar, Matrix &Pinf,
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const MatrixConstView &dataView,
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MatrixView &detrendedDataView)
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{
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initialize(steadyState, deepParams, R, Q, RQRt, T, dataView, detrendedDataView);
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setPstar(Pstar, Pinf, T, RQRt);
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}
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private:
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const double lyapunov_tol;
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const std::vector<size_t> zeta_varobs_back_mixed;
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//! Indices of back+mixed zetas inside varobs+back+mixed zetas
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std::vector<size_t> pi_bm_vbm;
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DetrendData detrendData;
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ModelSolution modelSolution;
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DiscLyapFast discLyapFast; //Lyapunov solver
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Matrix g_x;
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Matrix g_u;
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Matrix Rt, RQ;
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void setT(Matrix &T);
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template <class Mat1, class Mat2>
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void
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setRQR(Mat1 &R, const Mat2 &Q, Matrix &RQRt)
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{
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mat::assignByVectors(R, mat::nullVec, mat::nullVec, g_u, zeta_varobs_back_mixed, mat::nullVec);
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// Matrix RQRt=R*Q*R'
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blas::gemm("N", "N", 1.0, R, Q, 0.0, RQ); // R*Q
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blas::gemm("N", "T", 1.0, RQ, R, 0.0, RQRt); // R*Q*R'
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}
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void setPstar(Matrix &Pstar, Matrix &Pinf, const Matrix &T, const Matrix &RQRt) throw (DiscLyapFast::DLPException);
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};
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#endif // !defined(C3D996B8_22AB_4b77_B693_BA4777AFB091__INCLUDED_)
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