bdm::PF Class Reference

Trivial particle filter with proposal density equal to parameter evolution model. More...

#include <libPF.h>

Inheritance diagram for bdm::PF:

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List of all members.

Public Member Functions

 PF (const RV &rv0, mpdf &par0, mpdf &obs0, int n0)
 Default constructor.
void set_est (const epdf &epdf0)
 Set posterior density by sampling from epdf0.
void bayes (const vec &dt)
 Incremental Bayes rule.
vec * __w ()
 access function
virtual void bayesB (const mat &Dt)
 Batch Bayes rule (columns of Dt are observations).
virtual const epdf_epdf () const =0
 Returns a reference to the epdf representing posterior density on parameters.
virtual const epdf_e () const =0
 Returns a pointer to the epdf representing posterior density on parameters. Use with care!
virtual double logpred (const vec &dt) const
vec logpred_m (const mat &dt) const
 Matrix version of logpred.
virtual epdfpredictor (const RV &rv) const
 Constructs a predictive density (marginal density on data).
const RV_rv () const
 access function
double _ll () const
 access function
void set_evalll (bool evl0)
 access function
virtual BM_copy_ (bool changerv=false)

Protected Attributes

int n
 number of particles;
eEmp est
 posterior density
vec & _w
 pointer into eEmp
Array< vec > & _samples
 pointer into eEmp
mpdfpar
 Parameter evolution model.
mpdfobs
 Observation model.
RV rv
 Random variable of the posterior.
double ll
 Logarithm of marginalized data likelihood.
bool evalll
 If true, the filter will compute likelihood of the data record and store it in ll . Set to false if you want to save computational time.


Detailed Description

Trivial particle filter with proposal density equal to parameter evolution model.

Posterior density is represented by a weighted empirical density (eEmp ).


Member Function Documentation

void bdm::PF::bayes ( const vec &  dt  )  [virtual]

Incremental Bayes rule.

Parameters:
dt vector of input data

Implements bdm::BM.

Reimplemented in bdm::MPF< BM_T >.

References _samples, _w, est, bdm::mpdf::evallogcond(), n, obs, par, bdm::eEmp::resample(), and bdm::mpdf::samplecond().

virtual double bdm::BM::logpred ( const vec &  dt  )  const [inline, virtual, inherited]

Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.

Reimplemented in bdm::ARX, bdm::MixEF, and bdm::multiBM.

Referenced by bdm::BM::logpred_m().

virtual BM* bdm::BM::_copy_ ( bool  changerv = false  )  [inline, virtual, inherited]

Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype: BM* _copy_(){BM Tmp*=new Tmp(this*); return Tmp; }

Reimplemented in bdm::ARX, and bdm::BMEF.


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

Generated on Fri Feb 6 19:50:04 2009 for mixpp by  doxygen 1.5.6