BM Class Reference
Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. More...
#include <libBM.h>
Inheritance diagram for BM:
Collaboration diagram for BM:
Public Member Functions | |
| BM (const RV &rv0) | |
| Default constructor. | |
| virtual void | bayes (const vec &dt)=0 |
| Incremental Bayes rule. | |
| void | bayes (mat Dt) |
| Batch Bayes rule (columns of Dt are observations). | |
| virtual epdf & | _epdf ()=0 |
| Returns a pointer to the epdf representing posterior density on parameters. Use with care! | |
| virtual | ~BM () |
| Destructor for future use;. | |
| const RV & | _rv () const |
| access function | |
| double | _ll () const |
| access function | |
Protected Attributes | |
| 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. | |
Detailed Description
Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.
Member Function Documentation
| virtual void BM::bayes | ( | const vec & | dt | ) | [pure virtual] |
Incremental Bayes rule.
- Parameters:
-
dt vector of input data
Implemented in Kalman< sq_T >, KalmanCh, EKFfull, EKF< sq_T >, EKFCh, PF, MPF< BM_T >, ARX, EKFfixed, Kalman< ldmat >, Kalman< chmat >, and Kalman< fsqmat >.
The documentation for this class was generated from the following file:
- work/mixpp/bdm/stat/libBM.h
