bdm::mgnorm< sq_T > Class Template Reference

Mpdf with general function for mean value. More...

#include <exp_family.h>

List of all members.

Public Member Functions
	mgnorm ()
	default constructor
void	set_parameters (const shared_ptr< fnc > &g0, const sq_T &R0)
	set mean function
void	condition (const vec &cond)
	Update iepdf so that it represents this mpdf conditioned on rvc = cond This function provides convenient reimplementation in offsprings.
void	from_setting (const Setting &set)
void	validate ()
	This method TODO.
enorm< sq_T > &	e ()
	access function to iepdf
vec	samplecond (const vec &cond)
	Reimplements samplecond using condition().
double	evallogcond (const vec &val, const vec &cond)
	Reimplements evallogcond using condition().
virtual vec	evallogcond_m (const mat &Dt, const vec &cond)
	Efficient version of evallogcond for matrices.
virtual vec	evallogcond_m (const Array< vec > &Dt, const vec &cond)
	Efficient version of evallogcond for Array<vec>.
virtual mat	samplecond_m (const vec &cond, int N)
	Efficient version of samplecond.
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.
Access to attributes
const RV &	_rv () const
const RV &	_rvc () const
int	dimension () const
int	dimensionc ()
Connection to other objects
void	set_rvc (const RV &rvc0)
void	set_rv (const RV &rv0)
bool	isnamed ()
Protected Member Functions
void	set_ep (epdf &iepdf)
	set internal pointer ep to point to given iepdf
void	set_ep (epdf *iepdfp)
	set internal pointer ep to point to given iepdf
Protected Attributes
enorm< sq_T >	iepdf
	Internal epdf used for sampling.
int	dimc
	dimension of the condition
RV	rvc
	random variable in condition

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Detailed Description

template<class sq_T>
class bdm::mgnorm< sq_T >

Mpdf with general function for mean value.

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Member Function Documentation

template<class sq_T >

void bdm::mgnorm< sq_T >::from_setting

(

const Setting &

set

)

[inline, virtual]

Create Normal density with given function of mean value

from structure

                class = 'mgnorm';
                g.class =  'fnc';      // function for mean value evolution
                g._fields_of_fnc = ...;

                R = [1, 0;             // covariance matrix
                        0, 1];
                        --OR --
                dR = [1, 1];           // diagonal of cavariance matrix

                rv = RV({'name'})      // description of RV
                rvc = RV({'name'})     // description of RV in condition

Reimplemented from bdm::mpdf.

References bdm::UI::get(), bdm::mgnorm< sq_T >::set_parameters(), and bdm::mgnorm< sq_T >::validate().

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

• exp_family.h