bdm::BM Class Reference

Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities. More...

#include <bdmbase.h>

Public Member Functions
void	from_setting (const Setting &set)
	This method arrange instance properties according the data stored in the Setting structure.
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.
virtual void	validate ()
	This method TODO.
Constructors

	BM ()
	BM (const BM &B)
virtual BM *	_copy_ () const
Mathematical operations

virtual void	bayes (const vec &dt)=0
	Incremental Bayes rule.
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)
virtual const epdf &	posterior () const =0
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
RV	rvc
	Name of extension variable.
const RV &	_rvc () const
	access function
virtual void	condition (const vec &val)
	Substitute `val` for `rvc`.
Logging of results

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.
virtual void	set_options (const string &opt)
	Set boolean options from a string, recognized are: "logbounds,logll".
virtual void	log_add (logger &L, const string &name="")
	Add all logged variables to a logger.
virtual void	logit (logger &L)

Detailed Description

Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.

This object represents exact or approximate evaluation of the Bayes rule:

$f(\theta_t | d_1,\ldots,d_t) = \frac{f(y_t|\theta_t,\cdot) f(\theta_t|d_1,\ldots,d_{t-1})}{f(y_t|d_1,\ldots,d_{t-1})}$

Access to the resulting posterior density is via function posterior().

As a "side-effect" it also evaluates log-likelihood of the data, which can be accessed via function _ll(). It can also evaluate predictors of future values of $y_t$ , see functions epredictor() and predictor().

Alternatively, it can evaluate posterior density conditioned by a known constant, $ c_t $ :

$f(\theta_t | c_t, d_1,\ldots,d_t) \propto f(y_t,\theta_t|c_t,\cdot, d_1,\ldots,d_{t-1})$

The value of $ c_t $ is set by function condition().

Member Function Documentation

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

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::KalmanCh, bdm::EKFCh, and bdm::BMEF.

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

Incremental Bayes rule.

Parameters:

dt

vector of input data

Implemented in bdm::ARX, bdm::KalmanFull, bdm::KalmanCh, bdm::EKFfull, bdm::EKFCh, bdm::MultiModel, bdm::MixEF, bdm::PF, bdm::MPF< BM_T >, bdm::mexBM, bdm::BMEF, and bdm::multiBM.

Referenced by bayesB().

virtual double bdm::BM::logpred ( const vec & dt ) const [inline, virtual]

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 logpred_m().

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

bdmbase.h
bdmbase.cpp

bdm::BM Class Reference

Public Member Functions

Protected Attributes

Extension to conditional BM

Logging of results

Detailed Description

Member Function Documentation