EKFfull Class Reference

Extended Kalman Filter in full matrices. More...

#include <libKF.h>

Inheritance diagram for EKFfull:

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Collaboration diagram for EKFfull:

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List of all members.

Public Member Functions
	EKFfull (RV rvx, RV rvy, RV rvu)
	Default constructor.
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	set_est (vec mu0, mat P0)
	set estimates
epdf &	_epdf ()
	dummy!
void	bayes (mat Dt)
	Batch Bayes rule (columns of Dt are observations).
const RV &	_rv () const
	access function
double	_ll () 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
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.
Friends
std::ostream &	operator<< (std::ostream &os, const KalmanFull &kf)
	print elements of KF

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Detailed Description

Extended Kalman Filter in full matrices.

An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.

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

• work/mixpp/bdm/estim/libKF.h
• work/mixpp/bdm/estim/libKF.cpp