enorm< sq_T > Class Template Reference

Gaussian density with positive definite (decomposed) covariance matrix. More...

#include <libEF.h>

Inheritance diagram for enorm< sq_T >:

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Collaboration diagram for enorm< sq_T >:

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List of all members.

Public Member Functions
	enorm (RV &rv)
	Default constructor.
void	set_parameters (const vec &mu, const sq_T &R)
	Set mean value mu and covariance R.
void	tupdate (double phi, mat &vbar, double nubar)
	tupdate in exponential form (not really handy)
void	dupdate (mat &v, double nu=1.0)
	dupdate in exponential form (not really handy)
vec	sample () const
	Returns the required moment of the epdf.
mat	sample (int N) const
	TODO is it used?
double	eval (const vec &val) const
	Compute probability of argument val.
double	evalpdflog (const vec &val) const
	Compute log-probability of argument val.
vec	mean () const
	return expected value
vec *	_mu ()
	returns a pointer to the internal mean value. Use with Care!
void	_R (sq_T *&pR, sq_T *&piR)
	returns pointers to the internal variance and its inverse. Use with Care!
void	_cached (bool what)
	set cache as inconsistent
RV	_rv () const
	access function
Protected Attributes
vec	mu
	mean value
sq_T	R
	Covariance matrix in decomposed form.
sq_T	_iR
	Cache: _iR = inv(R);.
bool	cached
	indicator if _iR is chached
int	dim
	dimension (redundant from rv.count() for easier coding )
RV	rv
	Identified of the random variable.

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Detailed Description

template<class sq_T>
class enorm< sq_T >

Gaussian density with positive definite (decomposed) covariance matrix.

More?...

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Member Function Documentation

template<class sq_T>

vec enorm< sq_T >::sample

(

)

const [inline, virtual]

Returns the required moment of the epdf.

Returns a sample from the density,

Implements epdf.

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

• work/mixpp/bdm/stat/libEF.h

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