bdm::mpdf Class Reference

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

#include <libBM.h>

List of all members.

Public Member Functions

virtual string to_string ()
 This method returns a basic info about the current instance.
virtual void from_setting (const Setting &root)
 This method arrange instance properties according the data stored in the Setting structure.
virtual void to_setting (Setting &root) const
 This method save all the instance properties into the Setting structure.
virtual void validate ()
 This method TODO.
Constructors
 mpdf ()
 mpdf (const mpdf &m)
 copy constructor does not set pointer ep - has to be done in offsprings!
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 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.
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

int dimc
 dimension of the condition
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  )  [inline, virtual]

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 condition(), 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]

Returns.

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

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


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

Generated on Wed Jun 17 14:13:29 2009 for mixpp by  doxygen 1.5.8