bdm::EKFCh_unQ Class Reference

#include <ekf_templ.h>

Inheritance diagram for bdm::EKFCh_unQ:

bdm::EKFCh bdm::BMcond bdm::KalmanCh bdm::bdmroot bdm::Kalman< chmat > bdm::BM bdm::bdmroot

List of all members.


Detailed Description

Extended Kalman filter in Choleski form with unknown Q.

Public Member Functions

 EKFCh_unQ (RV rx, RV ry, RV ru, RV rQ)
 Default constructor.
void condition (const vec &Q0)
 Substitute val for rvc.
void set_parameters (diffbifn *pfxu, diffbifn *phxu, const chmat Q0, const chmat R0)
 Set nonlinear functions for mean values and covariance matrices.
void set_parameters (const mat &A0, const mat &B0, const mat &C0, const mat &D0, const chmat &Q0, const chmat &R0)
 Set parameters with check of relevance.
void bayes (const vec &dt)
 Here dt = [yt;ut] of appropriate dimensions.
void set_statistics (const vec &mu0, const chmat &P0)
void set_est (const vec &mu0, const chmat &P0)
 Set estimate values, used e.g. in initialization.
const epdfposterior () const
 access function
const enorm< chmat > * _e () const
mat & __K ()
 access function
vec _dP ()
 access function
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 epdfepredictor () const
 Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $.
virtual mpdfpredictor () 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)

Protected Attributes

diffbifnpfxu
 Internal Model f(x,u).
diffbifnphxu
 Observation Model h(x,u).
mat preA
 pre array (triangular matrix)
mat postA
 post array (triangular matrix)
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.
enorm< chmatest
 posterior density on $x_t$
enorm< chmatfy
 preditive density on $y_t$
mat _K
 placeholder for Kalman gain
vec & _yp
 cache of fy.mu
chmat_Ry
 cache of fy.R
vec & _mu
 cache of est.mu
chmat_P
 cache of est.R
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.
RV rvc
 Identificator of the conditioning variable.

Member Function Documentation

virtual BM* bdm::BM::_copy_ (  )  [inline, virtual, inherited]

Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype:

 BM* _copy_(){return new BM(*this);} 

Reimplemented in bdm::ARX.

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().


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

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