bdm::MPF Class Reference

Marginalized Particle filter. More...

#include <particles.h>

List of all members.

Classes

class mpfepdf

internal class for MPDF providing composition of eEmp with external components

Public Member Functions

MPF ()

Default constructor.

void set_parameters (shared_ptr< mpdf > par0, shared_ptr< mpdf > obs0, int n0, RESAMPLING_METHOD rm=SYSTEMATIC)

void set_BM (const BM &BMcond0)

void bayes (const vec &dt)

Incremental Bayes rule.

const epdf & posterior () const

void set_options (const string &opt)

const BM * _BM (int i)

Access function.

void from_setting (const Setting &set)

void validate ()

This method TODO.

virtual string to_string ()

This method returns a basic info about the current instance.

virtual void to_setting (Setting &set) const

This method save all the instance properties into the Setting structure.

Constructors

virtual BM * _copy_ () const

Mathematical operations

virtual void bayesB (const mat &Dt)

Batch Bayes rule (columns of Dt are observations).

virtual double logpred (const vec &dt) const

vec logpred_m (const mat &dt) const

Matrix version of logpred.

virtual epdf * epredictor () const

Constructs a predictive density $f(d_{t+1} |d_{t}, \ldots d_{0})$ .

virtual mpdf * predictor () const

Constructs conditional density of 1-step ahead predictor $f(d_{t+1} |d_{t+h-1}, \ldots d_{t})$ .

Access to attributes

const RV & _drv () const

void set_drv (const RV &rv)

void set_rv (const RV &rv)

double _ll () const

void set_evalll (bool evl0)

Protected Attributes

RV drv

Random variable of the data (optional).

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.

Extension to conditional BM

This extension is useful e.g. in Marginalized Particle Filter (bdm::MPF). Alternatively, it can be used for automated connection to DS when the condition is observed

const RV & _rvc () const

access function

virtual void condition (const vec &val)

Substitute val for rvc.

RV rvc

Name of extension variable.

Logging of results

virtual void log_add (logger &L, const string &name="")

Add all logged variables to a logger.

virtual void logit (logger &L)

ivec LIDs

IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].

ivec LFlags

Flags for logging - same size as LIDs, each entry correspond to the same in LIDs.

Detailed Description

Marginalized Particle filter.

A composition of particle filter with exact (or almost exact) bayesian models (BMs). The Bayesian models provide marginalized predictive density. Internaly this is achieved by virtual class MPFmpdf.

Member Function Documentation

virtual BM* bdm::BM::_copy_ ( ) const [inline, virtual, inherited]

Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype:

 BM* _copy_() const {return new BM(*this);}

Reimplemented in bdm::ARX, bdm::ARXfrg, bdm::KalmanCh, bdm::EKFCh, and bdm::BMEF.

void bdm::MPF::bayes ( const vec & dt ) [virtual]

Incremental Bayes rule.

Parameters:

dt

vector of input data

Implements bdm::BM.

References bdm::BM::condition().

void bdm::MPF::from_setting ( const Setting & set ) [inline, virtual]

configuration structure for basic PF

        BM              = BM_class;           // Bayesian filtr for analytical part of the model
        parameter_pdf   = mpdf_class;         // transitional pdf for non-parametric part of the model
        prior           = epdf_class;         // prior probability density
        --- optional ---
        n               = 10;                 // number of particles
        resmethod       = 'systematic', or 'multinomial', or 'stratified'
                                                                                  // resampling method

Reimplemented from bdm::BM.

References bdm::UI::get(), set_options(), and validate().

virtual double bdm::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 bdm::ARX, bdm::MixEF, and bdm::multiBM.

References bdm_error.

Referenced by bdm::BM::logpred_m().

void bdm::MPF::set_options ( const string & opt ) [inline, virtual]

Extends options understood by BM::set_options by option

logmeans - meaning

Reimplemented from bdm::BM.

Referenced by from_setting().

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

particles.h
particles.cpp


Classes
class	mpfepdf
	internal class for MPDF providing composition of eEmp with external components
Public Member Functions
	MPF ()
	Default constructor.
void	set_parameters (shared_ptr< mpdf > par0, shared_ptr< mpdf > obs0, int n0, RESAMPLING_METHOD rm=SYSTEMATIC)
void	set_BM (const BM &BMcond0)
void	bayes (const vec &dt)
	Incremental Bayes rule.
const epdf &	posterior () const
void	set_options (const string &opt)
const BM *	_BM (int i)
	Access function.
void	from_setting (const Setting &set)
void	validate ()
	This method TODO.
virtual string	to_string ()
	This method returns a basic info about the current instance.
virtual void	to_setting (Setting &set) const
	This method save all the instance properties into the Setting structure.
Constructors
virtual BM *	_copy_ () const
Mathematical operations
virtual void	bayesB (const mat &Dt)
	Batch Bayes rule (columns of Dt are observations).
virtual double	logpred (const vec &dt) const
vec	logpred_m (const mat &dt) const
	Matrix version of logpred.
virtual epdf *	epredictor () const
	Constructs a predictive density $f(d_{t+1} \|d_{t}, \ldots d_{0})$ .
virtual mpdf *	predictor () const
	Constructs conditional density of 1-step ahead predictor $f(d_{t+1} \|d_{t+h-1}, \ldots d_{t})$ .
Access to attributes
const RV &	_drv () const
void	set_drv (const RV &rv)
void	set_rv (const RV &rv)
double	_ll () const
void	set_evalll (bool evl0)
Protected Attributes
RV	drv
	Random variable of the data (optional).
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.
Extension to conditional BM
This extension is useful e.g. in Marginalized Particle Filter (bdm::MPF). Alternatively, it can be used for automated connection to DS when the condition is observed
const RV &	_rvc () const
	access function
virtual void	condition (const vec &val)
	Substitute `val` for `rvc`.
RV	rvc
	Name of extension variable.
Logging of results
virtual void	log_add (logger &L, const string &name="")
	Add all logged variables to a logger.
virtual void	logit (logger &L)
ivec	LIDs
	IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].
ivec	LFlags
	Flags for logging - same size as LIDs, each entry correspond to the same in LIDs.