Q and R.  
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#include <ekf_templ.h>
Public Member Functions | |
| void | condition (const vec &QR0) | 
Substitute val for rvc.  | |
| void | set_parameters (diffbifn *pfxu, diffbifn *phxu, const mat Q0, const mat R0) | 
| Set nonlinear functions for mean values and covariance matrices.  | |
| void | bayes (const vec &dt) | 
| Here dt = [yt;ut] of appropriate dimensions.  | |
| void | set_statistics (vec mu0, mat P0) | 
| set estimates  | |
| const epdf & | posterior () const | 
| dummy!  | |
| const enorm< fsqmat > * | _e () const | 
| const mat | _R () | 
| virtual string | ToString () | 
| This method returns a basic info about the current instance.  | |
| virtual void | from_setting (const Setting &root) | 
| This method arrange instance properties according the data stored in the Setting structure.  | |
| virtual void | to_setting (Setting &root) const | 
| This method save all the instance properties into the Setting structure.  | |
Constructors  | |
| virtual BM * | _copy_ () const | 
Mathematical operations  | |
| 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) | 
Public Attributes | |
| vec | mu | 
| Mean value of the posterior density.  | |
| mat | P | 
| Variance of the posterior density.  | |
| bool | evalll | 
| double | ll | 
Protected Attributes | |
| diffbifn * | pfxu | 
| Internal Model f(x,u).  | |
| diffbifn * | phxu | 
| Observation Model h(x,u).  | |
| enorm< fsqmat > | E | 
| int | dimx | 
| int | dimy | 
| int | dimu | 
| mat | A | 
| mat | B | 
| mat | C | 
| mat | D | 
| mat | R | 
| mat | Q | 
| mat | _Pp | 
| mat | _Ry | 
| mat | _iRy | 
| mat | _K | 
| 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.  | |
| double | ll | 
| Logarithm of marginalized data likelihood.  | |
| RV | drv | 
| Random variable of the data (optional).  | |
Friends | |
| std::ostream & | operator<< (std::ostream &os, const KalmanFull &kf) | 
| print elements of KF  | |
Extension to conditional BM | |
| This extension is useful e.g. in Marginalized Particle Filter (bdm::MPF). Alternatively, it can be used for automated connection to DS when the condition is observed  | |
| const RV & | _rvc () const | 
| access function  | |
| RV | rvc | 
| Name of extension variable.  | |
Logging of results | |
| virtual void | set_options (const string &opt) | 
| Set boolean options from a string recognized are: "logbounds,logll".  | |
| virtual void | log_add (logger &L, const string &name="") | 
| Add all logged variables to a logger.  | |
| virtual void | logit (logger &L) | 
| ivec | LIDs | 
| IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].  | |
| ivec | LFlags | 
| Flags for logging - same size as LIDs, each entry correspond to the same in LIDs.  | |
Q and R. | virtual BM* bdm::BM::_copy_ | ( | ) |  const [inline, virtual, inherited] | 
        
Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype:
BM* _copy_() const {return new BM(*this);}
Reimplemented in bdm::ARX, bdm::KalmanCh, bdm::EKF< sq_T >, bdm::EKFCh, and bdm::BMEF.
| virtual double bdm::BM::logpred | ( | const vec & | dt | ) |  const [inline, virtual, inherited] | 
        
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 bdm::BM::logpred_m().
 1.5.8