bdm::mpdf Class Reference

Conditional probability density, e.g. modeling some dependencies. More...

#include <libBM.h>

Inheritance diagram for bdm::mpdf:

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Collaboration diagram for bdm::mpdf:

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List of all members.

Public Member Functions

virtual vec samplecond (const vec &cond, double &ll)
 Returns a sample from the density conditioned on cond, $x \sim epdf(rv|cond)$.
virtual mat samplecond_m (const vec &cond, vec &ll, int N)
 Returns.
virtual void condition (const vec &cond)
 Update ep so that it represents this mpdf conditioned on rvc = cond.
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 ~mpdf ()
 Destructor for future use;.
 mpdf (const RV &rv0, const RV &rvc0)
 Default constructor.
RV _rvc () const
 access function
RV _rv () const
 access function
epdf_epdf ()
 access function
epdf_e ()
 access function

Protected Attributes

RV rv
 modeled random variable
RV rvc
 random variable in condition
epdfep
 pointer to internal epdf


Detailed Description

Conditional probability density, e.g. modeling some dependencies.

Member Function Documentation

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

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

Parameters:
cond is numeric value of rv
ll is a return value of log-likelihood of the sample.

Reimplemented in bdm::mprod.

References condition(), ep, bdm::epdf::evallog(), 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,
vec &  ll,
int  N 
) [inline, virtual]

Returns.

Parameters:
N samples from the density conditioned on cond, $x \sim epdf(rv|cond)$.
cond is numeric value of rv
ll is a return value of log-likelihood of the sample.

References condition(), bdm::RV::count(), ep, bdm::epdf::evallog(), rv, and bdm::epdf::sample().


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

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