Changeset 970

Timestamp:

05/23/10 11:39:58 (14 years ago)

Author:

smidl

Message:

Student + arx corrections

Location:

library

Files:

• bdm/estim/arx_ext.h (modified) (2 diffs)
• bdm/stat/exp_family.cpp (modified) (1 diff)
• bdm/stat/exp_family.h (modified) (2 diffs)
• tests/testsuite/estudent.cfg (modified) (1 diff)

library/bdm/estim/arx_ext.h

@@ -55 +55 @@
         \code
         class = 'ARXg';
-        rv    = RV({names_of_dt} )                 // description of output variables
+        yrv   = RV({names_of_dt} )                 // description of output variables
         rgr   = RV({names_of_regressors}, [-1,-2]} // description of regressor variables
         constant = 1;                              // 0/1 switch if the constant term is modelled or not
@@ -64 +64 @@
         alternative = {class='egiw',...};          // Alternative density in stabilized estimation, when not given prior is used
 
-        frg = 1.0;                                 // forgetting, default frg=1.0
+        frg   = 1.0;                               // forgetting, default frg=1.0
 
-        rv_param   = RV({names_of_parameters}}     // description of parametetr names
-                                                                                           // default: ["theta_i" and "r_i"]
+        rv    = RV({names_of_parameters}}          // description of parametetr names
         \endcode
         */

library/bdm/stat/exp_family.cpp

@@ -298 +298 @@
 
 void egiw::log_register ( bdm::logger& L, const string& prefix ) {
-        if ( log_level[logmean] || log_level[logvariance] ) { 
-                root::log_register ( L, prefix );
-                int th_dim = dimension() - dimx * ( dimx + 1 ) / 2;
-
-                if ( log_level[logmean] )
-                        L.add_vector( log_level, logmean, RV ( th_dim ), prefix ); 
-                if ( log_level[logvariance] )
-                        L.add_vector( log_level, logvariance, RV ( th_dim * th_dim ), prefix );
-        } else {
-                epdf::log_register ( L, prefix );
+        epdf::log_register ( L, prefix );
+        if ( log_level[logvartheta] ) { 
+                int th_dim = dim - dimx*dimx; // dimension - dimension of cov
+                L.add_vector( log_level, logvartheta, RV ( th_dim ), prefix ); 
         }
 }
 
 void egiw::log_write() const {
-        if ( log_level[logmean] || log_level[logvariance] ) { 
+        epdf::log_write();
+        if ( log_level[logvartheta] ) { 
                 mat M;
                 ldmat Lam;
                 ldmat Vz;
                 factorize ( M, Vz, Lam );
-                if( log_level[logmean] )
-                        log_level.store( logmean, est_theta() );
-                if( log_level[logvariance] )
-                        log_level.store( logvariance, cvectorize ( est_theta_cov().to_mat() ) );
-        } else {
-                epdf::log_write();
+                if( log_level[logvartheta] )
+                        log_level.store( logvartheta, cvectorize ( est_theta_cov().to_mat() ) );
         }
 }

library/bdm/stat/exp_family.h

@@ -296 +296 @@
                 
                 vec mean() const {return mu;}
-                mat covariance() const {return delta/(delta-2)*H.to_mat();}
+                mat covariance() const {
+                        return delta/(delta-2)*H.to_mat();
+                }
                 vec variance() const {return diag(covariance());}
                         //! \name access
@@ -338 +340 @@
 */
 class egiw : public eEF {
-        //! \var log_level_enums logvariance
-        //! TODO DOPLNIT
-
-        //! \var log_level_enums logmean
-        //! TODO DOPLNIT
-        LOG_LEVEL(egiw,logmean, logvariance);
+        //! \var log_level_enums logvartheta
+        //! Log variance of the theta part 
+
+        LOG_LEVEL(egiw,logvartheta);
 
 protected:

library/tests/testsuite/estudent.cfg

@@ -6 +6 @@
          mu = [1];
     H = ( "matrix", 1, 1, [ 1.0 ] );
-    delta = 3.0;
+    delta = 6.0;
   };
   mean = [1];
-  variance = [3.0];
-  R = ("matrix",1,1,[3.0]);
+  variance = [1.5];
+  R = ("matrix",1,1,[1.5]);
   support = {
         class = "rectangular_support";
-        ranges = ( [ -12.0, 12.0 ] );
+        ranges = ( [ -10.0, 12.0 ] );
         gridsizes = [ 100 ];
         };