bdm::multiBM Class Reference

#include <libEF.h>

Inheritance diagram for bdm::multiBM:

List of all members.

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Detailed Description

Estimator for Multinomial density.

Public Member Functions
	multiBM ()
	Default constructor.
	multiBM (const multiBM &B)
	Copy constructor.
void	set_statistics (const BM *mB0)
	Sets sufficient statistics to match that of givefrom mB0.
void	bayes (const vec &dt)
	Incremental Bayes rule.
double	logpred (const vec &dt) const
void	flatten (const BMEF *B)
	Flatten the posterior according to the given BMEF (of the same type!).
const epdf &	posterior () const
const eDirich *	_e () const
void	set_parameters (const vec &beta0)
virtual void	set_statistics (const BMEF *BM0)
	get statistics from another model
virtual void	bayes (const vec &data, const double w)
	Weighted update of sufficient statistics (Bayes rule).
BMEF *	_copy_ (bool changerv=false)
	Flatten the posterior as if to keep nu0 data.
Constructors
virtual BM *	_copy_ ()
Mathematical operations
virtual void	bayesB (const mat &Dt)
	Batch Bayes rule (columns of Dt are observations).
vec	logpred_m (const mat &dt) const
	Matrix version of logpred.
virtual epdf *	epredictor () const
	Constructs a predictive density .
virtual mpdf *	predictor () const
	Constructs a conditional density 1-step ahead predictor.
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
eDirich	est
	Conjugate prior and posterior.
vec &	beta
	Pointer inside est to sufficient statistics.
double	frg
	forgetting factor
double	last_lognc
	cached value of lognc() in the previous step (used in evaluation of ll )
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.

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Member Function Documentation

void bdm::multiBM::bayes

(

const vec &

dt

)

[inline, virtual]

Incremental Bayes rule.

Parameters:

dt

vector of input data

Reimplemented from bdm::BMEF.

References beta, est, bdm::BM::evalll, bdm::BMEF::frg, bdm::BMEF::last_lognc, bdm::BM::ll, and bdm::eDirich::lognc().

double bdm::multiBM::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 from bdm::BM.

References bdm::eDirich::_beta(), beta, est, bdm::BM::evalll, bdm::BMEF::frg, bdm::BMEF::last_lognc, and bdm::eDirich::lognc().

virtual BM* bdm::BM::_copy_

(

)

[inline, virtual, inherited]

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

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

Reimplemented in bdm::ARX.

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

• libEF.h