KalmanFull Class Reference

Basic Kalman filter with full matrices (education purpose only)! Will be deleted soon! More...

#include <libKF.h>

Inheritance diagram for KalmanFull:

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Collaboration diagram for KalmanFull:

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List of all members.

Public Member Functions
	KalmanFull (mat A, mat B, mat C, mat D, mat R, mat Q, mat P0, vec mu0)
	Full constructor.
void	bayes (const vec &dt, bool evalll=true)
	Here dt = [yt;ut] of appropriate dimensions.
virtual void	bayes (const vec &dt)=0
	Incremental Bayes rule.
void	bayes (mat Dt)
	Batch Bayes rule (columns of Dt are observations).
epdf *	_epdf ()
	Returns a pointer to the epdf representing posterior density on parameters. Use with care!
Public Attributes
vec	mu
	Mean value of the posterior density.
mat	P
	Variance of the posterior density.
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)

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Detailed Description

Basic Kalman filter with full matrices (education purpose only)! Will be deleted soon!

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Member Function Documentation

virtual void BM::bayes

(

const vec &

dt

)

[pure virtual, inherited]

Incremental Bayes rule.

Parameters:

dt

vector of input data

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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

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