EKFful_unQR Class Reference

Extended Kalman filter with unknown Q and R. More...

#include <ekf_templ.h>

Inheritance diagram for EKFful_unQR:

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Collaboration diagram for EKFful_unQR:

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List of all members.

Public Member Functions
	EKFful_unQR (RV rx, RV ry, RV ru, RV rQR)
	Default constructor.
void	condition (const vec &QR0)
	Substitute val for rvc.
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	bayes (mat Dt)
	Batch Bayes rule (columns of Dt are observations).
void	set_est (vec mu0, mat P0)
	set estimates
epdf &	_epdf ()
	dummy!
const RV &	_rv () const
	access function
double	_ll () const
	access function
const RV &	_rvc () 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
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.
double	ll
	Logarithm of marginalized data likelihood.
RV	rv
	Random variable of the posterior.
RV	rvc
	Identificator of the conditioning variable.
Friends
std::ostream &	operator<< (std::ostream &os, const KalmanFull &kf)
	print elements of KF

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Detailed Description

Extended Kalman filter with unknown Q and R.

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

• work/git/mixpp/bdm/estim/ekf_templ.h