#include <ekf_obj.h>
An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.
Public Member Functions | |
void | init_ekf (double Tv) |
void | ekf (double ux, double uy, double isxd, double isyd) |
void | prediction (int *ux) |
void | correction (void) |
void | update_psi (void) |
EKFfixed () | |
Default constructor. | |
void | bayes (const vec &dt) |
Here dt = [yt;ut] of appropriate dimensions. | |
epdf & | posterior () |
dummy! | |
void | condition (const vec &Q0) |
Substitute val for rvc . | |
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) |
virtual const epdf & | posterior () const =0 |
virtual const epdf * | _e () const =0 |
Public Attributes | |
int | Q [16] |
int | R [4] |
int | x_est [4] |
int | x_pred [4] |
int | P_pred [16] |
int | P_est [16] |
int | Y_mes [2] |
int | ukalm [2] |
int | Kalm [8] |
int | PSI [16] |
int | temp15a [16] |
int | cA |
int | cB |
int | cC |
int | cG |
int | cH |
long | temp30a [4] |
enorm< fsqmat > | E |
mat | Ry |
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. | |
int | dimc |
dimension of the conditioning variable | |
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().