Changeset 1121

Timestamp:

06/29/10 15:58:04 (14 years ago)

Author:

smidl

Message:

Preparation for ARX with linear forgetting

Location:

library/bdm

Files:

• estim/arx.h (modified) (1 diff)
• stat/exp_family.h (modified) (1 diff)

library/bdm/estim/arx.h

@@ -209 +209 @@
 SHAREDPTR ( ARX );
 
+//! \brief ARX moidel with parameters in LS form
+class ARXls : public BMEF{
+        egw_ls<ldmat> est;
+        
+        const egw_ls<ldmat>& posterior() {return est;};
+        
+        void bayes(const vec &dt, const vec &psi){
+        }
+};
+
 /*! \brief ARX model conditined by knowledge of the forgetting factor
 \f[ f(    heta| d_1 \ldots d_t , \phi_t) \f]

library/bdm/stat/exp_family.h

@@ -514 +514 @@
 SHAREDPTR ( egiw );
 
+//! \brief Gauss-Wishart with recursion on moments
+//! Using precision as parameter
+//! following notation of [Karny Andrysek 2009], precision
+template<class sq_T>
+class egw_ls: public eEF{
+        public:
+                vec theta;
+                sq_T P;
+                double omega;
+                double nu;
+                
+                vec mean() const{
+                        return concat(theta, omega);
+                }
+                mat covariance() const {
+                        sq_T tmp=P;
+                        tmp*=nu/((nu-2)*omega);
+                        return tmp.to_mat();//<======= error - missing omega
+                }
+                vec variance() const {
+                        return diag(covariance());//<======= error - missing omega
+                }
+                vec sample() const NOT_IMPLEMENTED(vec(0));
+                double lognc() const {return 0.0;} //TODO
+};
+
 /*! \brief Dirichlet posterior density