EKFfull Class Reference
Extended Kalman Filter in full matrices. More...
#include <libKF.h>
Inheritance diagram for EKFfull:
Collaboration diagram for EKFfull:
Public Member Functions | |
| EKFfull (RV rvx, RV rvy, RV rvu) | |
| Default constructor. | |
| 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_est (vec mu0, mat P0) |
| set estimates | |
| epdf & | _epdf () |
| dummy! | |
| void | bayes (mat Dt) |
| Batch Bayes rule (columns of Dt are observations). | |
| const RV & | _rv () const |
| access function | |
| double | _ll () 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 |
| 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. | |
Friends | |
| std::ostream & | operator<< (std::ostream &os, const KalmanFull &kf) |
| print elements of KF | |
Detailed Description
Extended Kalman Filter in full matrices.An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.
The documentation for this class was generated from the following files:
- work/mixpp/bdm/estim/libKF.h
- work/mixpp/bdm/estim/libKF.cpp
