bdm::egamma Class Reference

Gamma posterior density. More...

#include <exp_family.h>

List of all members.

Public Member Functions

vec sample () const
 Returns a sample, $ x $ from density $ f_x()$.
double evallog (const vec &val) const
 TODO: is it used anywhere?
double lognc () const
 logarithm of the normalizing constant, $\mathcal{I}$
vec & _alpha ()
 Returns poiter to alpha and beta. Potentially dengerous: use with care!
vec & _beta ()
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 void dupdate (mat &v)
 TODO decide if it is really needed.
virtual double evallog_nn (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 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 $ 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 mpdfcondition (const RV &rv) const
 Return conditional density on the given RV, the remaining rvs will be in conditioning.
virtual epdfmarginal (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.


Detailed Description

Gamma posterior density.

Multivariate Gamma density as product of independent univariate densities.

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


Member Function Documentation

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

Load from structure with elements:

 { alpha = [...];         // vector of alpha
   beta = [...];          // vector of beta
   rv = {class="RV",...}  // description
 }

Reimplemented from bdm::epdf.

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


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

Generated on Wed Jul 1 13:05:57 2009 for mixpp by  doxygen 1.5.8