mlnorm< sq_T > Class Template Reference

Normal distributed linear function with linear function of mean value;. More...

#include <libEF.h>

Inheritance diagram for mlnorm< sq_T >:

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Collaboration diagram for mlnorm< sq_T >:

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List of all members.

Public Member Functions
	mlnorm (RV &rv, RV &rvc)
	Constructor.
void	set_parameters (const mat &A, const sq_T &R)
	Set A and R.
vec	samplecond (vec &cond, double &lik)
	Generate one sample of the posterior.
mat	samplecond (vec &cond, vec &lik, int n)
	Generate matrix of samples of the posterior.
void	condition (vec &cond)
	Set value of rvc . Result of this operation is stored in epdf use function _ep to access it.
virtual vec	samplecond (const vec &cond, double &ll)
	Returns the required moment of the epdf.
virtual mat	samplecond (const vec &cond, vec &ll, int N)
	Returns.
virtual void	condition (const vec &cond)
	Update ep so that it represents this mpdf conditioned on rvc = cond.
virtual double	evalcond (const vec &dt, const vec &cond)
	Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently.
RV	_rvc ()
	access function
RV	_rv ()
	access function
epdf &	_epdf ()
	access function
Protected Attributes
RV	rv
	modeled random variable
RV	rvc
	random variable in condition
epdf *	ep
	pointer to internal epdf

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Detailed Description

template<class sq_T>
class mlnorm< sq_T >

Normal distributed linear function with linear function of mean value;.

Mean value .

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Member Function Documentation

virtual vec mpdf::samplecond	(	const vec &	cond,
		double &	ll
	)			[inline, virtual, inherited]

Returns the required moment of the epdf.

Returns a sample from the density conditioned on cond, .

Parameters:

	cond	is numeric value of rv
	ll	is a return value of log-likelihood of the sample.

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

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

virtual mat mpdf::samplecond	(	const vec &	cond,
		vec &	ll,
		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 mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().

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

• work/git/mixpp/bdm/stat/libEF.h