#include <libBM.h>

Public Member Functions | |
Constructors | |
| BM () | |
| BM (const BM &B) | |
| virtual BM * | _copy_ () |
Mathematical operations | |
| virtual void | bayes (const vec &dt)=0 |
| Incremental Bayes rule. | |
| virtual void | bayesB (const mat &Dt) |
| Batch Bayes rule (columns of Dt are observations). | |
| virtual double | logpred (const vec &dt) const |
| vec | logpred_m (const mat &dt) const |
| Matrix version of logpred. | |
| virtual epdf * | epredictor () const |
Constructs a predictive density . | |
| virtual mpdf * | predictor () const |
| Constructs a conditional density 1-step ahead predictor. | |
Access to attributes | |
| const RV & | _drv () const |
| void | set_drv (const RV &rv) |
| void | set_rv (const RV &rv) |
| double | _ll () const |
| void | set_evalll (bool evl0) |
| virtual const epdf & | posterior () const =0 |
| virtual const epdf * | _e () const =0 |
Protected Attributes | |
| RV | drv |
| Random variable of the data (optional). | |
| double | ll |
| Logarithm of marginalized data likelihood. | |
| bool | 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 computational time. | |
| virtual BM* bdm::BM::_copy_ | ( | ) | [inline, virtual] |
| virtual void bdm::BM::bayes | ( | const vec & | dt | ) | [pure virtual] |
Incremental Bayes rule.
| dt | vector of input data |
Implemented in bdm::ARX, bdm::Kalman< sq_T >, bdm::KalmanCh, bdm::EKFfull, bdm::EKF< sq_T >, bdm::EKFCh, bdm::PF, bdm::MPF< BM_T >, bdm::MixEF, bdm::BMEF, bdm::multiBM, bdm::Kalman< ldmat >, bdm::Kalman< chmat >, and bdm::Kalman< fsqmat >.
Referenced by bayesB().
| virtual double bdm::BM::logpred | ( | const vec & | dt | ) | const [inline, virtual] |
Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
Reimplemented in bdm::ARX, bdm::MixEF, and bdm::multiBM.
Referenced by logpred_m().
1.5.6