Kalman< sq_T > Class Template Reference

Kalman filter with covariance matrices in square root form. More...

#include <libKF.h>

Inheritance diagram for Kalman< sq_T >:

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Collaboration diagram for Kalman< sq_T >:

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List of all members.

Public Member Functions
	Kalman (RV rvx0, RV rvy0, RV rvu0)
	Default constructor.
	Kalman (const Kalman< sq_T > &K0)
	Copy constructor.
void	set_parameters (const mat &A0, const mat &B0, const mat &C0, const mat &D0, const sq_T &R0, const sq_T &Q0)
	Set parameters with check of relevance.
void	set_est (const vec &mu0, const sq_T &P0)
	Set estimate values, used e.g. in initialization.
void	bayes (const vec &dt)
	Here dt = [yt;ut] of appropriate dimensions.
epdf &	_epdf ()
	Returns a pointer to the epdf representing posterior density on parameters. Use with care!
void	bayes (mat Dt)
	Batch Bayes rule (columns of Dt are observations).
Protected Attributes
RV	rvy
RV	rvu
int	dimx
int	dimy
int	dimu
mat	A
mat	B
mat	C
mat	D
sq_T	R
sq_T	Q
enorm< sq_T >	est
	posterior density on $x_t$
enorm< sq_T >	fy
	preditive density on $y_t$
mat	_K
vec *	_yp
sq_T *	_Ry
sq_T *	_iRy
vec *	_mu
sq_T *	_P
sq_T *	_iP
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.

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Detailed Description

template<class sq_T>
class Kalman< sq_T >

Kalman filter with covariance matrices in square root form.

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

• work/mixpp/bdm/estim/libKF.h

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