bdm::eiWishartCh Class Reference

Inverse Wishart on Choleski decomposition. More...

#include <exp_family.h>

List of all members.

Public Member Functions

void set_parameters (const mat &Y0, const double delta0)
 constructor function
vec sample () const
 Returns a sample, $ x $ from density $ f_x()$.
void _setY (const vec &y0)
 access function
virtual double evallog (const vec &val) const
 Compute log-probability of argument val In case the argument is out of suport return -Infinity.
void from_setting (const Setting &set)
 Load from structure with elements:.
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
Construction of each epdf should support two types of constructors:
  • empty constructor,
  • copy constructor,
The following constructors should be supported for convenience: 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 shared_ptr< mpdfcondition (const RV &rv) const
 Return conditional density on the given RV, the remaining rvs will be in conditioning.
virtual shared_ptr< epdfmarginal (const RV &rv) const
 Return marginal density on the given RV, the remainig rvs are intergrated out.
virtual vec mean () const
 return expected value
virtual vec variance () const
 return expected variance (not covariance!)
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

eWishartCh W
 Internal instance of Wishart density.
int p
 size of Ch
double delta
 parameter delta
int dim
 dimension of the random variable
RV rv
 Description of the random variable.


Detailed Description

Inverse Wishart on Choleski decomposition.

Being computed by conversion from `standard' Wishart


Member Function Documentation

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

Load from structure with elements:.

         { rv = {class="RV", names=(...),}; // RV describing meaning of random variable
           // elements of offsprings
         }

Reimplemented from bdm::root.

Reimplemented in bdm::enorm< sq_T >, bdm::egiw, bdm::eDirich, bdm::egamma, bdm::euni, bdm::merger_base, bdm::merger_mix, bdm::enorm< ldmat >, bdm::enorm< chmat >, and bdm::enorm< fsqmat >.

References bdm::epdf::set_rv().


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

Generated on Wed Oct 7 17:34:49 2009 for mixpp by  doxygen 1.5.9