#include <libKF.h>

| Public Member Functions | |
| KFcondR () | |
| Default constructor. | |
| void | condition (const vec &R) | 
| Substitute valforrvc. | |
| void | set_parameters (const mat &A0, const mat &B0, const mat &C0, const mat &D0, const ldmat &Q0, const ldmat &R0) | 
| Set parameters with check of relevance. | |
| void | set_est (const vec &mu0, const ldmat &P0) | 
| Set estimate values, used e.g. in initialization. | |
| void | bayes (const vec &dt) | 
| Here dt = [yt;ut] of appropriate dimensions. | |
| const epdf & | posterior () const | 
| access function | |
| const enorm< ldmat > * | _e () const | 
| mat & | __K () | 
| access function | |
| vec | _dP () | 
| access function | |
| const RV & | _rvc () const | 
| access function | |
| Constructors | |
| virtual BM * | _copy_ () | 
| 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) | 
| Protected Attributes | |
| RV | rvy | 
| Indetifier of output rv. | |
| RV | rvu | 
| Indetifier of exogeneous rv. | |
| int | dimx | 
| cache of rv.count() | |
| int | dimy | 
| cache of rvy.count() | |
| int | dimu | 
| cache of rvu.count() | |
| mat | A | 
| Matrix A. | |
| mat | B | 
| Matrix B. | |
| mat | C | 
| Matrix C. | |
| mat | D | 
| Matrix D. | |
| ldmat | Q | 
| Matrix Q in square-root form. | |
| ldmat | R | 
| Matrix R in square-root form. | |
| enorm< ldmat > | est | 
| posterior density on $x_t$ | |
| enorm< ldmat > | fy | 
| preditive density on $y_t$ | |
| mat | _K | 
| placeholder for Kalman gain | |
| vec & | _yp | 
| cache of fy.mu | |
| ldmat & | _Ry | 
| cache of fy.R | |
| vec & | _mu | 
| cache of est.mu | |
| ldmat & | _P | 
| cache of est.R | |
| 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. | |
| RV | rvc | 
| Identificator of the conditioning variable. | |
| virtual BM* bdm::BM::_copy_ | ( | ) |  [inline, virtual, inherited] | 
| 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().
 1.5.6
 1.5.6