PF BM MPF< BM_T > libPF.h int int PF::n n number of particles; MPF< BM_T >::bayes bayes MPF< BM_T >::set_est set_est eEmp eEmp PF::est est posterior density MPF< BM_T >::bayes bayes vec & vec& PF::_w _w pointer into eEmp MPF< BM_T >::bayes bayes Array< vec > & Array<vec>& PF::_samples _samples pointer into eEmp MPF< BM_T >::bayes bayes MPF< BM_T >::set_est set_est mpdf & mpdf& PF::par par Parameter evolution model. MPF< BM_T >::bayes bayes mpdf & mpdf& PF::obs obs Observation model. bayes RV RV BM::rv rv Random variable of the posterior. BM::_rv MPF< BM_T >::MPF EKFfull::set_parameters ARX::structure_est double double BM::ll ll Logarithm of marginalized data likelihood. BM::_ll EKFfixed::bayes EKF< sq_T >::bayes Kalman< sq_T >::bayes EKFCh::bayes KalmanCh::bayes EKFfull::bayes ARX::bayes bool bool BM::evalll evalll If true, the filter will compute likelihood of the data record and store it in ll . Set to false if you want to save time. EKFfixed::bayes EKF< sq_T >::bayes Kalman< sq_T >::bayes EKFCh::bayes KalmanCh::bayes EKFfull::bayes ARX::bayes PF::PF (const RV &rv0, mpdf &par0, mpdf &obs0, int n0) PF const RV & rv0 mpdf & par0 mpdf & obs0 int n0 Default constructor. void void PF::set_est (const epdf &epdf0) set_est set_est const epdf & epdf0 Set posterior density by sampling from epdf0. _samples n epdf::sample MPF< BM_T >::set_est void void PF::bayes (const vec &dt) bayes bayes bayes const vec & dt Incremental Bayes rule. dt vector of input data _samples _w est mpdf::evalcond n obs par eEmp::resample mpdf::samplecond void void BM::bayes (mat Dt) bayes mat Dt Batch Bayes rule (columns of Dt are observations). epdf & virtual epdf& BM::_epdf ()=0 _epdf _epdf _epdf _epdf _epdf _epdf _epdf _epdf _epdf Returns a pointer to the epdf representing posterior density on parameters. Use with care! const RV & const RV& BM::_rv () const _rv access function BM::rv double double BM::_ll () const _ll access function BM::ll Trivial particle filter with proposal density equal to parameter evolution model. Posterior density is represented by a weighted empirical density (eEmp ). BM MPF< BM_T > PF epdf rv BM rv PF obs par est eEmp RV mpdf rv rvc ep PF_epdf PF_ll PF_rv PF_samples PF_w PFbayes PFbayes PFBM PFest PFevalll PFll PFn PFobs PFpar PFPF PFrv PFset_est PF~BM