bdm::eDirich Class Reference

Dirichlet posterior density. More...

#include <libEF.h>

Inheritance diagram for bdm::eDirich:

Collaboration diagram for bdm::eDirich:

List of all members.

Public Member Functions

eDirich (const RV &rv, const vec &beta0)

Default constructor.

eDirich (const eDirich &D0)

Copy constructor.

vec sample () const

Returns a sample, $x$ from density $epdf(rv)$ .

vec mean () const

return expected value

vec variance () const

return expected variance (not covariance!)

double evallog_nn (const vec &val) const

In this instance, val is ...

double lognc () const

logarithm of the normalizing constant, $\mathcal{I}$

vec & _beta ()

access function

void set_parameters (const vec &beta0)

Set internal parameters.

virtual void dupdate (mat &v)

TODO decide if it is really needed.

virtual double evallog (const vec &val) const

Evaluate normalized log-probability.

virtual vec evallog (const mat &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 mat sample_m (int N) const

Returns N samples from density $epdf(rv)$ .

virtual vec evallog_m (const mat &Val) 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.

const RV & _rv () const

access function, possibly dangerous!

void _renewrv (const RV &in_rv)

modifier function - useful when copying epdfs

Protected Attributes

vec beta

sufficient statistics

double gamma

speedup variable

RV rv

Identified of the random variable.

Detailed Description

Dirichlet posterior density.

Continuous Dirichlet density of $n$ -dimensional variable $x$

$f(x|\beta) = \frac{\Gamma[\gamma]}{\prod_{i=1}^{n}\Gamma(\beta_i)} \prod_{i=1}^{n}x_i^{\beta_i-1}$

where $\gamma=\sum_i \beta_i$ .

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

libEF.h


Public Member Functions
	eDirich (const RV &rv, const vec &beta0)
	Default constructor.
	eDirich (const eDirich &D0)
	Copy constructor.
vec	sample () const
	Returns a sample, from density .
vec	mean () const
	return expected value
vec	variance () const
	return expected variance (not covariance!)
double	evallog_nn (const vec &val) const
	In this instance, val is ...
double	lognc () const
	logarithm of the normalizing constant, $\mathcal{I}$
vec &	_beta ()
	access function
void	set_parameters (const vec &beta0)
	Set internal parameters.
virtual void	dupdate (mat &v)
	TODO decide if it is really needed.
virtual double	evallog (const vec &val) const
	Evaluate normalized log-probability.
virtual vec	evallog (const mat &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 mat	sample_m (int N) const
	Returns N samples from density .
virtual vec	evallog_m (const mat &Val) 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.
const RV &	_rv () const
	access function, possibly dangerous!
void	_renewrv (const RV &in_rv)
	modifier function - useful when copying epdfs
Protected Attributes
vec	beta
	sufficient statistics
double	gamma
	speedup variable
RV	rv
	Identified of the random variable.