bdm::mlstudent Class Reference

#include <exp_family.h>

List of all members.

Public Member Functions

void set_parameters (const mat &A0, const vec &mu0, const ldmat &R0, const ldmat &Lambda0)
void condition (const vec &cond)
vec & _mu_const ()
 access function
mat & _A ()
 access function
mat _R ()
 access function
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
void set_parameters (const mat &A, const vec &mu0, const ldmat &R)
 Set A and R.
Matematical operations
virtual vec samplecond (const vec &cond)
 Returns a sample from the density conditioned on cond, $x \sim epdf(rv|cond)$.
virtual mat samplecond_m (const vec &cond, int N)
 Returns.
virtual double evallogcond (const vec &dt, const vec &cond)
 Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently.
virtual vec evallogcond_m (const mat &Dt, const vec &cond)
 Matrix version of evallogcond.
virtual vec evallogcond_m (const Array< vec > &Dt, const vec &cond)
 Array<vec> version of evallogcond.
Access to attributes
RV _rv ()
RV _rvc ()
int dimension ()
int dimensionc ()
epdf_epdf ()
epdf_e ()
Connection to other objects
void set_rvc (const RV &rvc0)
void set_rv (const RV &rv0)
bool isnamed ()

Protected Attributes

ldmat Lambda
ldmat_R
ldmat Re
enorm< ldmatepdf
 Internal epdf that arise by conditioning on rvc.
mat A
vec mu_const
vec & _mu
int dimc
 dimension of the condition
RV rvc
 random variable in condition
epdfep
 pointer to internal epdf

Friends

std::ostream & operator<< (std::ostream &os, mlnorm< sq_M > &ml)


Detailed Description

(Approximate) Student t density with linear function of mean value

The internal epdf of this class is of the type of a Gaussian (enorm). However, each conditioning is trying to assure the best possible approximation by taking into account the zeta function. See [] for reference.

Perhaps a moment-matching technique?


Member Function Documentation

void bdm::mlstudent::condition ( const vec &  cond  )  [inline, virtual]

Set value of rvc . Result of this operation is stored in epdf use function _ep to access it.

Reimplemented from bdm::mlnorm< ldmat >.

References bdm::mlnorm< ldmat >::_R(), ldmat::invqform(), and ldmat::rows().

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

Load from structure with elements:

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

Reimplemented from bdm::root.

Reimplemented in bdm::mepdf, bdm::mprod, bdm::mgnorm< sq_T >, bdm::mgamma, bdm::migamma_ref, and bdm::mlognorm.

virtual vec bdm::mpdf::samplecond ( const vec &  cond  )  [inline, virtual, inherited]

Returns a sample from the density conditioned on cond, $x \sim epdf(rv|cond)$.

Parameters:
cond is numeric value of rv

Reimplemented in bdm::mprod.

References bdm::mpdf::condition(), bdm::mpdf::ep, and bdm::epdf::sample().

Referenced by bdm::MPF< BM_T >::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().

virtual mat bdm::mpdf::samplecond_m ( const vec &  cond,
int  N 
) [inline, virtual, inherited]

Returns.

Parameters:
N samples from the density conditioned on cond, $x \sim epdf(rv|cond)$.
cond is numeric value of rv

References bdm::mpdf::condition(), bdm::epdf::dimension(), bdm::mpdf::ep, and bdm::epdf::sample().


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

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