Changeset 1176 for library

Timestamp:

09/02/10 14:40:42 (14 years ago)

Author:

smidl

Message:

student epredictor in ARX

Location:

library

Files:

• bdm/estim/arx.cpp (modified) (1 diff)
• bdm/estim/arx.h (modified) (2 diffs)
• tests/stresssuite/arx_elem_stress.cpp (modified) (1 diff)
• tests/stresssuite/arx_stress.cpp (modified) (1 diff)

library/bdm/estim/arx.cpp

@@ -144 +144 @@
 }
 
-mlstudent* ARX::predictor_student ( ) const {
+estudent<ldmat>* ARX::epredictor_student ( const vec &cond ) const {
+        bdm_assert_debug ( cond.length() == rgrlen , "ARX::epredictor cond is of size "+num2str(cond.length())+" expected dimension is "+num2str(rgrlen) );
+        
+        mat mu ( dimy, posterior()._V().rows() - dimy );
+        
+        vec ext_rgr;
+        if (have_constant) {
+                ext_rgr = concat(cond,vec_1(1.0));
+        } else {
+                ext_rgr = cond;
+        }
+        
+        estudent<ldmat>* tmp = new estudent<ldmat> ( );
+        //TODO: too hackish
+        if ( yrv._dsize() > 0 ) {
+        }
+
+        ldmat Lam;
+        ldmat Vz;
+
+        est.factorize( mu, Vz, Lam ); //mu =
+        //correction for student-t  -- TODO check if correct!!
+        double zeta =0;
+        if (mu.cols()>0) {// nonempty egiw
+                mat p_mu = mu.T() * ext_rgr;    //the result is one column
+                tmp->_mu()= p_mu.get_col ( 0 );
+                zeta = Vz.invqform(ext_rgr);
+        } else {
+                tmp->_mu()=zeros(dimy);
+        }
+        // nu-rgrlen+2+dimy = delta+dimy
+        tmp->_delta()=est._nu()+2-rgrlen;
+        tmp->_H()=Lam;
+        tmp->_H()*=1/tmp->_delta();
+        tmp->_H()*=(1+zeta);
+        
+        if (dimy==yrv._dsize())
+                tmp->set_rv(yrv);
+        return tmp;
+}
+
+mlstudent* ARX::predictor ( ) const {
     const ldmat &V = posterior()._V();
 

library/bdm/estim/arx.h

@@ -93 +93 @@
     //! Conditioned version of the predictor
     enorm<ldmat>* epredictor ( const vec &rgr ) const;
-    //! conditional version of the predictor
+        estudent<ldmat>* epredictor_student ( const vec &rgr ) const;
+        //! conditional version of the predictor
     template<class sq_T>
     shared_ptr<mlnorm<sq_T> > ml_predictor() const;
@@ -99 +100 @@
     template<class sq_T>
     void ml_predictor_update ( mlnorm<sq_T> &pred ) const;
-    mlstudent* predictor_student() const;
+    mlstudent* predictor() const;
     //! Brute force structure estimation.\return indices of accepted regressors.
     ivec structure_est ( const egiw &Eg0 );

library/tests/stresssuite/arx_elem_stress.cpp

@@ -39 +39 @@
     X2.set_row ( 0, x );
 
-    mlstudent* Ap = Ar.predictor_student();
+    mlstudent* Ap = Ar.predictor();
     vec Ap_x = Ap->evallogcond_mat ( X, empty_vec );
     vec ll_x = Ar.logpred_mat ( X2 , empty_vec);

library/tests/stresssuite/arx_stress.cpp

@@ -55 +55 @@
 
         // Build predictor
-        mlstudent*      Pr = Ar.predictor_student ( );
-        // Test similarity of likelihoods from the Bayes rule and the predictor
+        mlstudent*      Pr = Ar.predictor ( );
+                estudent<ldmat>*        PrS = Ar.epredictor_student (rgr );
+                
+                cout << "m1: " << Pr->_A()*rgr+Pr->_mu_const() << 
+                " v1:" << Pr->e()._R();
+                cout << "ms: " << PrS->mean() << " vs:" << PrS->variance()  << 
+                " del:" << PrS->_delta() <<endl;
+                
+                // Test similarity of likelihoods from the Bayes rule and the predictor
         cout << "BR log-lik: " << Ar._ll();
-        cout << " , predictor ll: " <<  Pr->evallogcond ( vec_1 ( Yt ( t ) ), rgr )  << endl;
-        delete Pr;
-    }
+                cout << " , predictor ll: " <<  Pr->evallogcond ( vec_1 ( Yt ( t ) ), rgr );
+                cout << " , epredictor_student ll: " <<  PrS->evallog ( vec_1 ( Yt ( t ) ) )  << endl;
+                delete Pr;
+                delete PrS;
+        }
     //print posterior moments
     cout << "posterior mean: " << f_thr.mean() << endl;