EKF_unQ Class Reference

Extended Kalman filter with unknown Q. More...

Inheritance diagram for EKF_unQ:

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List of all members.

Public Member Functions

 EKF_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 ldmatQ0, const ldmatR0)
 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 ldmat &R0, const ldmat &Q0)
 Set parameters with check of relevance.
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 (const vec &mu0, const ldmat &P0)
 Set estimate values, used e.g. in initialization.
epdf_epdf ()
 access function
const RV_rv () const
 access function
double _ll () const
 access function
const RV_rvc () 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.
ldmat Q
 Matrix Q in square-root form.
ldmat R
 Matrix R in square-root form.
enorm< ldmatest
 posterior density on $x_t$
enorm< ldmatfy
 preditive density on $y_t$
mat _K
 placeholder for Kalman gain
vec * _yp
 cache of fy.mu
ldmat_Ry
 cache of fy.R
ldmat_iRy
 cache of fy.iR
vec * _mu
 cache of est.mu
ldmat_P
 cache of est.R
ldmat_iP
 cache of est.iR
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.
RV rvc
 Identificator of the conditioning variable.


Detailed Description

Extended Kalman filter with unknown Q.
The documentation for this class was generated from the following file:
Generated on Wed Mar 12 16:15:49 2008 for mixpp by  doxygen 1.5.3