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 ()
	access function
void	bayes (mat Dt)
	Batch Bayes rule (columns of Dt are observations).
const RV &	_rv () const
	access function
double	_ll () 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.
sq_T	Q
	Matrix Q in square-root form.
sq_T	R
	Matrix R in square-root form.
enorm< sq_T >	est
	posterior density on $x_t$
enorm< sq_T >	fy
	preditive density on $y_t$
mat	_K
	placeholder for Kalman gain
vec *	_yp
	cache of fy.mu
sq_T *	_Ry
	cache of fy.R
sq_T *	_iRy
	cache of fy.iR
vec *	_mu
	cache of est.mu
sq_T *	_P
	cache of est.R
sq_T *	_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.

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Detailed Description

template<class sq_T>
class Kalman< sq_T >

Kalman filter with covariance matrices in square root form.

Parameter evolution model:

Observation model:

Where $e_t$ and $w_t$ are independent vectors Normal(0,1)-distributed disturbances.

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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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