root/bdm/estim/merger.h @ 182

/*!
  \file
  \brief Mergers for combination of pdfs
  \author Vaclav Smidl.

  -----------------------------------
  BDM++ - C++ library for Bayesian Decision Making under Uncertainty

  Using IT++ for numerical operations
  -----------------------------------
*/

#ifndef MER_H
#define MER_H

#include <itpp/itbase.h>
#include "mixef.h"

using namespace itpp;
using std::string;

/*!
@brief Function for general combination of pdfs

Mixtures of Gaussian densities are used internally. Switching to other densities should be trivial.
*/

class merger : public compositepdf, public epdf {
protected:
        //!Internal mixture of EF models
        MixEF Mix;
        //!Number of samples used in approximation
        int Ns;
        //!Number of components in a mixture
        int Nc;
        //!Prior on the log-normal merging model
        double beta;
public:
//!Default constructor
        merger ( const Array<mpdf*> &S ) :
                        compositepdf ( S ), epdf ( getrv ( false ) ),
                        Mix ( Array<BMEF*> ( 0 ),vec ( 0 ) )
        {setindices(rv); beta=2.0; Ns=100; Nc=10;}
        //! Set internal parameters used in approximation
        void set_parameters ( double beta0, int Ns0, int Nc0 ) {        beta=beta0;Ns=Ns0;Nc=Nc0;}
        //!Initialize the proposal density. This function must be called before merge()!
        void init() {
                Array<vec> Smps ( n );
                //Gibbs sampling
                for ( int i=0;i<n;i++ ) {Smps ( i ) =zeros ( 0 );}
        }
        //!Create a mixture density using known proposal
        void merge ( const epdf* g0 );
        //!Create a mixture density, make sure to call init() before the first call
        void merge () {merge ( & ( Mix._epdf() ) );};

        //! Merge log-likelihood values
        vec lognorm_merge ( mat &lW );
        //! sample from merged density
        //! weight w is a
        vec sample ( )const { return Mix._epdf().sample();}
        double evalpdflog ( const vec &dt ) const{ 
                vec dtf=ones(dt.length()+1);    
                dtf.set_subvector(0,dt); 
                return Mix.logpred ( dtf );}
        vec mean()const {return Mix._epdf().mean();}
        //! for future use
        virtual ~merger() {};
        
        //! Access function
        MixEF& _Mix() {return Mix;}
};



#endif // MER_H