Changeset 1064 for library/tests/stresssuite/arx_stress.cpp

Timestamp:

06/09/10 14:00:40 (15 years ago)

Author:

mido

Message:

astyle applied all over the library

Files:

• library/tests/stresssuite/arx_stress.cpp (modified) (1 diff)

library/tests/stresssuite/arx_stress.cpp

@@ -17 +17 @@
 
 TEST ( arx_stress ) {
-        // Setup model
-        vec th ( "0.8 -0.3 0.4 0.01" );
-        int ord = th.length(); //auxiliary variable
-        double sqr = 0.1;
+    // Setup model
+    vec th ( "0.8 -0.3 0.4 0.01" );
+    int ord = th.length(); //auxiliary variable
+    double sqr = 0.1;
 
-        //Test constructor
-        mat V0 = 0.00001 * eye ( ord + 1 );
-        V0 ( 0 ) = 1; //
-        double nu0 = ord + 5.0;
+    //Test constructor
+    mat V0 = 0.00001 * eye ( ord + 1 );
+    V0 ( 0 ) = 1; //
+    double nu0 = ord + 5.0;
 
-        ARX Ar;
-        Ar.set_statistics ( 1, V0, nu0 );               // Estimator
-        Ar.set_constant ( false );
-        Ar.validate();
-        const epdf& f_thr = Ar.posterior();          // refrence to posterior of the estimator
+    ARX Ar;
+    Ar.set_statistics ( 1, V0, nu0 );               // Estimator
+    Ar.set_constant ( false );
+    Ar.validate();
+    const epdf& f_thr = Ar.posterior();          // refrence to posterior of the estimator
 
-        //Test estimation
-        int ndat = 100;                 // number of data records
-        vec Yt ( ndat );                // Store generated data
-        Yt.set_subvector ( 0, randn ( ord ) ); //initial values
-        vec rgr ( ord );                // regressor
+    //Test estimation
+    int ndat = 100;                 // number of data records
+    vec Yt ( ndat );                // Store generated data
+    Yt.set_subvector ( 0, randn ( ord ) ); //initial values
+    vec rgr ( ord );                // regressor
 
-        //print moments of the prior distribution
-        cout << "prior mean: " << f_thr.mean() << endl;
-        cout << "prior variance: " << f_thr.variance() << endl;
+    //print moments of the prior distribution
+    cout << "prior mean: " << f_thr.mean() << endl;
+    cout << "prior variance: " << f_thr.variance() << endl;
 
-        // cycle over time:
-        for ( int t = ord; t < ndat; t++ ) {
-                //Generate regressor
-                for ( int j = 0; j < ( ord ); j++ ) {
-                        rgr ( j ) = Yt ( t - j - 1 );
-                }
-                //model
-                Yt ( t ) = th * rgr + sqr * NorRNG();
+    // cycle over time:
+    for ( int t = ord; t < ndat; t++ ) {
+        //Generate regressor
+        for ( int j = 0; j < ( ord ); j++ ) {
+            rgr ( j ) = Yt ( t - j - 1 );
+        }
+        //model
+        Yt ( t ) = th * rgr + sqr * NorRNG();
 
-                Ar.bayes ( vec_1 ( Yt ( t ) ), rgr );       // Bayes rule
+        Ar.bayes ( vec_1 ( Yt ( t ) ), rgr );       // Bayes rule
 
-                // Build predictor
-                mlstudent*      Pr = Ar.predictor_student ( );
-                // 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;
-        }
-        //print posterior moments
-        cout << "posterior mean: " << f_thr.mean() << endl;
-        cout << "posterior variance: " << f_thr.variance() << endl;
+        // Build predictor
+        mlstudent*      Pr = Ar.predictor_student ( );
+        // 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;
+    }
+    //print posterior moments
+    cout << "posterior mean: " << f_thr.mean() << endl;
+    cout << "posterior variance: " << f_thr.variance() << endl;
 
-        // Test brute-froce structure estimation
+    // Test brute-froce structure estimation
 
-        cout << "Structure estimation: " << endl;
-        cout << Ar.structure_est ( egiw ( 1, V0, nu0 ) ) << endl;
+    cout << "Structure estimation: " << endl;
+    cout << Ar.structure_est ( egiw ( 1, V0, nu0 ) ) << endl;
 }