bdm::euni Class Reference

Uniform distributed density on a rectangular support. More...

#include <exp_family.h>

List of all members.

Public Member Functions

double eval (const vec &val) const

double evallog (const vec &val) const

Compute log-probability of argument val.

vec sample () const

Returns a sample, $ x $ from density $ f_x()$ .

vec mean () const

set values of low and high

vec variance () const

return expected variance (not covariance!)

void from_setting (const Setting &set)

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.

virtual void validate ()

This method TODO.

Constructors

euni ()

euni (const vec &low0, const vec &high0)

void set_parameters (const vec &low0, const vec &high0)

Constructors

Construction of each epdf should support two types of constructors:

empty constructor,

copy constructor,

The following constructors should be supported for convenience:

constructor followed by calling set_parameters()

constructor accepting random variables calling set_rv()

All internal data structures are constructed as empty. Their values (including sizes) will be set by method set_parameters(). This way references can be initialized in constructors.

void set_parameters (int dim0)

Matematical Operations

virtual mat sample_m (int N) const

Returns N samples, $[x_1 , x_2 , \ldots \$ from density $ f_x(rv)$ .

virtual vec evallog_m (const mat &Val) const

Compute log-probability of multiple values argument val.

virtual vec evallog_m (const Array< vec > &Avec) const

Compute log-probability of multiple values argument val.

virtual mpdf * condition (const RV &rv) const

Return conditional density on the given RV, the remaining rvs will be in conditioning.

virtual epdf * marginal (const RV &rv) const

Return marginal density on the given RV, the remainig rvs are intergrated out.

virtual void qbounds (vec &lb, vec &ub, double percentage=0.95) const

Lower and upper bounds of percentage % quantile, returns mean-2*sigma as default.

Connection to other classes

Description of the random quantity via attribute rv is optional. For operations such as sampling rv does not need to be set. However, for marginalization and conditioning rv has to be set. NB:

void set_rv (const RV &rv0)

Name its rv.

bool isnamed () const

True if rv is assigned.

const RV & _rv () const

Return name (fails when isnamed is false).

Access to attributes

int dimension () const

Size of the random variable.

Protected Attributes

vec low

lower bound on support

vec high

upper bound on support

vec distance

internal

double nk

normalizing coefficients

double lnk

cache of log( nk )

int dim

dimension of the random variable

RV rv

Description of the random variable.

Detailed Description

Uniform distributed density on a rectangular support.

Member Function Documentation

void bdm::euni::from_setting ( const Setting & set ) [inline, virtual]

Load from structure with elements:

 { high = [...];          // vector of upper bounds
   low = [...];           // vector of lower bounds
   rv = {class="RV",...}  // description of RV
 }

Reimplemented from bdm::epdf.

References bdm::UI::get(), high, and low.

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

exp_family.h


Public Member Functions
double	eval (const vec &val) const
double	evallog (const vec &val) const
	Compute log-probability of argument `val`.
vec	sample () const
	Returns a sample, from density .
vec	mean () const
	set values of `low` and `high`
vec	variance () const
	return expected variance (not covariance!)
void	from_setting (const Setting &set)
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.
virtual void	validate ()
	This method TODO.
Constructors
	euni ()
	euni (const vec &low0, const vec &high0)
void	set_parameters (const vec &low0, const vec &high0)
Constructors
Construction of each epdf should support two types of constructors: empty constructor, copy constructor, The following constructors should be supported for convenience: constructor followed by calling `set_parameters()` constructor accepting random variables calling `set_rv()` All internal data structures are constructed as empty. Their values (including sizes) will be set by method `set_parameters()`. This way references can be initialized in constructors.
void	set_parameters (int dim0)
Matematical Operations
virtual mat	sample_m (int N) const
	Returns N samples, $[x_1 , x_2 , \ldots \$ from density .
virtual vec	evallog_m (const mat &Val) const
	Compute log-probability of multiple values argument `val`.
virtual vec	evallog_m (const Array< vec > &Avec) const
	Compute log-probability of multiple values argument `val`.
virtual mpdf *	condition (const RV &rv) const
	Return conditional density on the given RV, the remaining rvs will be in conditioning.
virtual epdf *	marginal (const RV &rv) const
	Return marginal density on the given RV, the remainig rvs are intergrated out.
virtual void	qbounds (vec &lb, vec &ub, double percentage=0.95) const
	Lower and upper bounds of `percentage` % quantile, returns mean-2*sigma as default.
Connection to other classes
Description of the random quantity via attribute `rv` is optional. For operations such as sampling `rv` does not need to be set. However, for `marginalization` and `conditioning` `rv` has to be set. NB:
void	set_rv (const RV &rv0)
	Name its rv.
bool	isnamed () const
	True if rv is assigned.
const RV &	_rv () const
	Return name (fails when isnamed is false).
Access to attributes
int	dimension () const
	Size of the random variable.
Protected Attributes
vec	low
	lower bound on support
vec	high
	upper bound on support
vec	distance
	internal
double	nk
	normalizing coefficients
double	lnk
	cache of log( `nk` )
int	dim
	dimension of the random variable
RV	rv
	Description of the random variable.