# EKFful_unQR Class Reference

Extended Kalman filter with unknown `Q` and `R`. More...

`#include <ekf_templ.h>`

Inheritance diagram for EKFful_unQR:

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Collaboration diagram for EKFful_unQR:

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List of all members.

## Public Member Functions
| EKFful_unQR (RV rx, RV ry, RV ru, RV rQR)
| Default constructor.
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 | bayes (mat Dt)
| Batch Bayes rule (columns of Dt are observations).
void | set_est (vec mu0, mat P0)
| set estimates
epdf & | _epdf ()
| dummy!
const RV & | _rv () const
| access function
double | _ll () const
| access function
const RV & | _rvc () const
| access function
## Public Attributes
vec | mu
| Mean value of the posterior density.
mat | P
| Variance of the posterior density.
bool | evalll
double | ll
## Protected Attributes
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 time.
double | ll
| Logarithm of marginalized data likelihood.
RV | rv
| Random variable of the posterior.
RV | rvc
| Identificator of the conditioning variable.
## Friends
std::ostream & | operator<< (std::ostream &os, const KalmanFull &kf)
| print elements of KF

## Detailed Description

Extended Kalman filter with unknown `Q` and `R`.

The documentation for this class was generated from the following file:

- work/mixpp/bdm/estim/ekf_templ.h