bdm::egamma Class Reference

Gamma posterior density. More...

Detailed Description

Gamma posterior density.

Multivariate Gamma density as product of independent univariate densities.

$f(x|\alpha,\beta) = \prod f(x_i|\alpha_i,\beta_i)$

#include <exp_family.h>

Public Member Functions
vec	sample () const
	Returns a sample, from density .
double	evallog (const vec &val) const
	Evaluate normalized log-probability.
double	lognc () const
	logarithm of the normalizing constant, $\mathcal{I}$
vec &	_alpha ()
	Returns pointer to internal alpha. Potentially dengerous: use with care!
vec &	_beta ()
	Returns pointer to internal beta. Potentially dengerous: use with care!
vec	mean () const
	return expected value
vec	variance () const
	return expected variance (not covariance!)
void	from_setting (const Setting &set)
void	validate ()
	This method TODO.
virtual double	evallog_nn (const vec &val) const
	Evaluate normalized log-probability.
virtual vec	evallog_m (const mat &Val) const
	Evaluate normalized log-probability for many samples.
virtual vec	evallog_m (const Array< vec > &Val) const
	Evaluate normalized log-probability for many samples.
virtual void	pow (double p)
	Power of the density, used e.g. to flatten the density.
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.
Constructors

	egamma ()
	egamma (const vec &a, const vec &b)
void	set_parameters (const vec &a, const vec &b)
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 shared_ptr< mpdf >	condition (const RV &rv) const
	Return conditional density on the given RV, the remaining rvs will be in conditioning.
virtual shared_ptr< 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	alpha
	Vector $\alpha$ .
vec	beta
	Vector $\beta$ .
int	dim
	dimension of the random variable
RV	rv
	Description of the random variable.

Member Function Documentation

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

Create Gamma density

$f(rv|rvc) = \Gamma(\alpha, \beta)$

from structure

                class = 'egamma';
                alpha = [...];         // vector of alpha
                beta = [...];          // vector of beta
                rv = RV({'name'})      // description of RV

Reimplemented from bdm::epdf.

References alpha, bdm::UI::get(), and validate().

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

exp_family.h
exp_family.cpp

bdm::egamma Class Reference

Detailed Description

Public Member Functions

Protected Attributes

Member Function Documentation