#include <libKF.h>
Public Member Functions | |
KalmanCh (RV rvx0, RV rvy0, RV rvu0) | |
Default constructor. | |
KalmanCh (const KalmanCh &K0) | |
Copy constructor. | |
void | set_parameters (const mat &A0, const mat &B0, const mat &C0, const mat &D0, const chmat &R0, const chmat &Q0) |
Set parameters with check of relevance. | |
void | set_pred (const vec &mu0, const chmat &P0) |
Set estimate values, used e.g. in initialization. | |
void | bayes (const vec &dt) |
Here dt = [yt;ut] of appropriate dimensions The following equality hold::
. | |
epdf & | _epdf () |
access function | |
epdf & | _pred () |
access function | |
void | bayes (mat Dt) |
Batch Bayes rule (columns of Dt are observations). | |
const RV & | _rv () const |
access function | |
double | _ll () const |
access function | |
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. | |
chmat | Q |
Matrix Q in square-root form. | |
chmat | R |
Matrix R in square-root form. | |
mat | preA |
pre array (triangular matrix) | |
mat | postA |
post array (triangular matrix) | |
enorm< chmat > | pred |
predictive density on $x_t$ | |
enorm< chmat > | fy |
predictive density on $y_t$ | |
vec * | _mu |
chmat * | _P |
vec * | _yp |
chmat * | _Ry |
RV | rv |
Random variable of the posterior. | |
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 time. |