PF Class Reference

Trivial particle filter with proposal density equal to parameter evolution model. More...

#include <libPF.h>

Inheritance diagram for PF:

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Collaboration diagram for PF:

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List of all members.

Public Member Functions
	PF (const RV &rv0, mpdf &par0, mpdf &obs0, int n0)
	Default constructor.
void	set_est (const epdf &epdf0)
	Set posterior density by sampling from epdf0.
void	bayes (const vec &dt)
	Incremental Bayes rule.
vec *	__w ()
	access function
virtual void	bayesB (const mat &Dt)
	Batch Bayes rule (columns of Dt are observations).
virtual const epdf &	_epdf () const =0
	Returns a reference to the epdf representing posterior density on parameters.
virtual const epdf *	_e () const =0
	Returns a pointer to the epdf representing posterior density on parameters. Use with care!
virtual double	logpred (const vec &dt) const
vec	logpred_m (const mat &dt) const
	Matrix version of logpred.
virtual epdf *	predictor (const RV &rv) const
	Constructs a predictive density (marginal density on data).
const RV &	_rv () const
	access function
double	_ll () const
	access function
void	set_evalll (bool evl0)
	access function
virtual BM *	_copy_ (bool changerv=false)
Protected Attributes
int	n
	number of particles;
eEmp	est
	posterior density
vec &	_w
	pointer into eEmp
Array< vec > &	_samples
	pointer into eEmp
mpdf &	par
	Parameter evolution model.
mpdf &	obs
	Observation model.
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 computational time.

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Detailed Description

Trivial particle filter with proposal density equal to parameter evolution model.

Posterior density is represented by a weighted empirical density (eEmp ).

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Member Function Documentation

void PF::bayes

(

const vec &

dt

)

[virtual]

Incremental Bayes rule.

Parameters:

dt

vector of input data

Implements BM.

Reimplemented in MPF< BM_T >.

References _samples, _w, est, mpdf::evallogcond(), n, obs, par, eEmp::resample(), and mpdf::samplecond().

virtual double BM::logpred

(

const vec &

dt

)

const [inline, virtual, inherited]

Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.

Reimplemented in ARX, MixEF, and multiBM.

Referenced by BM::logpred_m().

virtual BM* BM::_copy_

(

bool

changerv = false

)

[inline, virtual, inherited]

Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype: BM* _copy_(){BM Tmp*=new Tmp(this*); return Tmp; }

Reimplemented in ARX, and BMEF.

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

• work/git/mixpp/bdm/estim/libPF.h
• work/git/mixpp/bdm/estim/libPF.cpp