bdm::mlstudent Class Reference

#include <libEF.h>

Inheritance diagram for bdm::mlstudent:

List of all members.

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Detailed Description

(Approximate) Student t density with linear function of mean value

The internal epdf of this class is of the type of a Gaussian (enorm). However, each conditioning is trying to assure the best possible approximation by taking into account the zeta function. See [] for reference.

Perhaps a moment-matching technique?

Public Member Functions
void	set_parameters (const mat &A0, const vec &mu0, const ldmat &R0, const ldmat &Lambda0)
void	condition (const vec &cond)
vec &	_mu_const ()
	access function
mat &	_A ()
	access function
mat	_R ()
	access function
Constructors
void	set_parameters (const mat &A, const vec &mu0, const ldmat &R)
	Set A and R.
Matematical operations
virtual vec	samplecond (const vec &cond)
	Returns a sample from the density conditioned on cond, .
virtual mat	samplecond_m (const vec &cond, int N)
	Returns.
virtual double	evallogcond (const vec &dt, const vec &cond)
	Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently.
virtual vec	evallogcond_m (const mat &Dt, const vec &cond)
	Matrix version of evallogcond.
Access to attributes
RV	_rv ()
RV	_rvc ()
int	dimension ()
int	dimensionc ()
epdf &	_epdf ()
epdf *	_e ()
Connection to other objects
void	set_rvc (const RV &rvc0)
void	set_rv (const RV &rv0)
bool	isnamed ()
Protected Attributes
ldmat	Lambda
ldmat &	_R
ldmat	Re
enorm< ldmat >	epdf
	Internal epdf that arise by conditioning on rvc.
mat	A
vec	mu_const
vec &	_mu
int	dimc
	dimension of the condition
RV	rvc
	random variable in condition
epdf *	ep
	pointer to internal epdf
Friends
std::ostream &	operator<< (std::ostream &os, mlnorm< sq_M > &ml)

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Member Function Documentation

void bdm::mlstudent::condition

(

const vec &

cond

)

[inline, virtual]

Set value of rvc . Result of this operation is stored in epdf use function _ep to access it.

Reimplemented from bdm::mlnorm< ldmat >.

References bdm::mlnorm< ldmat >::_R(), ldmat::invqform(), and ldmat::rows().

virtual vec bdm::mpdf::samplecond

(

const vec &

cond

)

[inline, virtual, inherited]

Returns a sample from the density conditioned on cond, .

Parameters:

cond

is numeric value of rv

Reimplemented in bdm::mprod.

References bdm::mpdf::condition(), bdm::mpdf::ep, and bdm::epdf::sample().

Referenced by bdm::MPF< BM_T >::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().

virtual mat bdm::mpdf::samplecond_m	(	const vec &	cond,
		int	N
	)			[inline, virtual, inherited]

Returns.

Parameters:

	N	samples from the density conditioned on cond, .
	cond	is numeric value of rv
	ll	is a return value of log-likelihood of the sample.

References bdm::mpdf::condition(), bdm::epdf::dimension(), bdm::mpdf::ep, and bdm::epdf::sample().

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

• libEF.h