Changeset 271 for bdm/estim

Timestamp:

02/16/09 10:03:13 (15 years ago)

Author:

smidl

Message:

Next major revision

Location:

bdm/estim

Files:

• arx.h (modified) (2 diffs)
• libKF.cpp (modified) (3 diffs)
• libKF.h (modified) (6 diffs)
• libPF.h (modified) (3 diffs)
• merger.h (modified) (2 diffs)
• mixef.cpp (modified) (2 diffs)
• mixef.h (modified) (2 diffs)

bdm/estim/arx.h

@@ -31 +31 @@
 \f]
 
-Extension for time-variant parameters \f$\theta_t,r_t\f$ may be achived using exponential forgetting (Kulhavy and Zarrop, 1993). In such a case, the forgetting factor \c frg \f$\in <0,1>\f$ should be given in the constructor. Time-invariant parameters are estimated for \c frg = 1.
+See \ref tut_arx for mathematical treatment.
+
+The easiest way how to use the class is:
+\include arx_simple.cpp
+
 */
 class ARX: public BMEF {
@@ -89 +93 @@
         //!@{
         const egiw* _e() const {return &est ;};
-        const egiw& _epdf() const {return est;}
+        const egiw& posterior() const {return est;}
         //!@}
 

bdm/estim/libKF.cpp

@@ -6 +6 @@
 using std::endl;
 
-KalmanFull::KalmanFull ( mat A0, mat B0, mat C0, mat D0, mat R0, mat Q0, mat P0, vec mu0 ) {
+KalmanFull::KalmanFull ( mat A0, mat B0, mat C0, mat D0, mat Q0, mat R0, mat P0, vec mu0 ) {
         dimx = A0.rows();
         dimu = B0.cols();
@@ -15 +15 @@
         it_assert_debug ( C0.cols() ==dimx, "KalmanFull: C is not square" );
         it_assert_debug ( ( D0.rows() ==dimy ) || ( D0.cols() ==dimu ), "KalmanFull: D is not compatible" );
+        it_assert_debug ( ( Q0.cols() ==dimx ) || ( Q0.rows() ==dimx ), "KalmanFull: Q is not compatible" );
         it_assert_debug ( ( R0.cols() ==dimy ) || ( R0.rows() ==dimy ), "KalmanFull: R is not compatible" );
-        it_assert_debug ( ( Q0.cols() ==dimx ) || ( Q0.rows() ==dimx ), "KalmanFull: Q is not compatible" );
 
         A = A0;
@@ -116 +116 @@
 
 
-void KalmanCh::set_parameters ( const mat &A0,const mat &B0,const mat &C0,const mat &D0,const chmat &R0,const chmat &Q0 ) {
-
-        ( ( Kalman<chmat>* ) this )->set_parameters ( A0,B0,C0,D0,R0,Q0 );
+void KalmanCh::set_parameters ( const mat &A0,const mat &B0,const mat &C0,const mat &D0,const chmat &Q0,const chmat &R0 ) {
+
+        ( ( Kalman<chmat>* ) this )->set_parameters ( A0,B0,C0,D0,Q0,R0 );
         // Cholesky special!
-        preA.clear();
+        preA=zeros(dimy+dimx+dimx,dimy+dimx);
+//      preA.clear();
         preA.set_submatrix ( 0,0,R._Ch() );
         preA.set_submatrix ( dimy+dimx,dimy,Q._Ch() );

bdm/estim/libKF.h

@@ -109 +109 @@
         Kalman ( const Kalman<sq_T> &K0 );
         //! Set parameters with check of relevance
-        void set_parameters ( const mat &A0,const mat &B0,const mat &C0,const mat &D0,const sq_T &R0,const sq_T &Q0 );
+        void set_parameters ( const mat &A0,const mat &B0,const mat &C0,const mat &D0,const sq_T &Q0,const sq_T &R0 );
         //! Set estimate values, used e.g. in initialization.
         void set_est ( const vec &mu0, const sq_T &P0 ) {
@@ -121 +121 @@
         void bayes ( const vec &dt );
         //!access function
-        const epdf& _epdf() const {return est;}
+        const epdf& posterior() const {return est;}
         const enorm<sq_T>* _e() const {return &est;}
         //!access function
@@ -130 +130 @@
 
 /*! \brief Kalman filter in square root form
+
+Trivial example:
+\include kalman_simple.cpp
+ 
 */
 class KalmanCh : public Kalman<chmat>{
@@ -142 +146 @@
         KalmanCh ():Kalman<chmat>(),preA(),postA(){};
         //! Set parameters with check of relevance
-        void set_parameters ( const mat &A0,const mat &B0,const mat &C0,const mat &D0,const chmat &R0,const chmat &Q0 );
-        void set_est ( const vec &mu0, const chmat &P0 ) {
+        void set_parameters ( const mat &A0,const mat &B0,const mat &C0,const mat &D0,const chmat &Q0,const chmat &R0 );
+        void set_statistics ( const vec &mu0, const chmat &P0 ) {
                 est.set_parameters ( mu0,P0 );
         };
@@ -187 +191 @@
         void set_est (vec mu0, mat P0){mu=mu0;P=P0;};
         //!dummy!
-        const epdf& _epdf()const{return E;};
+        const epdf& posterior()const{return E;};
         const enorm<fsqmat>* _e()const{return &E;};
         const mat _R(){return P;}
@@ -281 +285 @@
 
 template<class sq_T>
-void Kalman<sq_T>::set_parameters ( const mat &A0,const  mat &B0, const mat &C0, const mat &D0, const sq_T &R0, const sq_T &Q0 ) {
+void Kalman<sq_T>::set_parameters ( const mat &A0,const  mat &B0, const mat &C0, const mat &D0, const sq_T &Q0, const sq_T &R0 ) {
+        dimx = A0.rows();
+        dimy = C0.rows();
+        dimu = B0.cols();
+        
         it_assert_debug ( A0.cols() ==dimx, "Kalman: A is not square" );
         it_assert_debug ( B0.rows() ==dimx, "Kalman: B is not compatible" );

bdm/estim/libPF.h

@@ -122 +122 @@
                 for ( int i=0;i<n;i++ ) {
                         Bms[i] = new BM_T ( BMcond0 ); //copy constructor
-                        const epdf& pom=Bms[i]->_epdf();
+                        const epdf& pom=Bms[i]->posterior();
                         jest.set_elements ( i,1.0/n,&pom );
                 }
@@ -131 +131 @@
 
         void bayes ( const vec &dt );
-        const epdf& _epdf() const {return jest;}
+        const epdf& posterior() const {return jest;}
         const epdf* _e() const {return &jest;} //Fixme: is it useful?
         //! Set postrior of \c rvc to samples from epdf0. Statistics of Bms are not re-computed! Use only for initialization!
@@ -195 +195 @@
                                 delete Bms[i];
                                 Bms[i] = new BM_T ( *Bms[ind ( i ) ] ); //copy constructor
-                                const epdf& pom=Bms[i]->_epdf();
+                                const epdf& pom=Bms[i]->posterior();
                                 jest.set_elements ( i,1.0/n,&pom );
                         }

bdm/estim/merger.h

@@ -81 +81 @@
         void merge ( const epdf* g0 );
 //!Create a mixture density, make sure to call init() before the first call
-        void merge () {merge ( & ( Mix._epdf() ) );};
+        void merge () {merge ( & ( Mix.posterior() ) );};
 
 //! Merge log-likelihood values
@@ -87 +87 @@
 //! sample from merged density
 //! weight w is a
-        vec sample ( ) const { return Mix._epdf().sample();}
+        vec sample ( ) const { return Mix.posterior().sample();}
         double evallog ( const vec &dt ) const {
                 vec dtf=ones ( dt.length() +1 );

bdm/estim/mixef.cpp

@@ -124 +124 @@
 double MixEF::logpred ( const vec &dt ) const {
 
-        vec w=weights._epdf().mean();
+        vec w=weights.posterior().mean();
         double exLL=0.0;
         for ( int i=0;i<n;i++ ) {
@@ -137 +137 @@
         emix* tmp;
         tmp = new emix (  );
-        tmp->set_parameters ( weights._epdf().mean(), pC, false );
+        tmp->set_parameters ( weights.posterior().mean(), pC, false );
         tmp->ownComs();
         return tmp;

bdm/estim/mixef.h

@@ -59 +59 @@
                 for ( int i=0;i<Coms.length();i++ ) {
 //                      it_assert_debug(!x,"MixEF::MixEF : Incompatible components");
-                        epdfs ( i ) =& ( Coms ( i )->_epdf() );
+                        epdfs ( i ) =& ( Coms ( i )->posterior() );
                 }
                 // last in the product is the weight
-                epdfs ( n ) =& ( weights._epdf() );
+                epdfs ( n ) =& ( weights.posterior() );
                 est = new eprod ( epdfs );
         }
@@ -104 +104 @@
         void bayesB ( const mat &dt, const vec &wData );
         double logpred ( const vec &dt ) const;
-        const epdf& _epdf() const {return *est;}
+        const epdf& posterior() const {return *est;}
         const eprod* _e() const {return est;}
         emix* epredictor() const;