MPF< BM_T > Class Template Reference

Marginalized Particle filter. More...

#include <libPF.h>

Inheritance diagram for MPF< BM_T >:

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List of all members.

Public Member Functions

 MPF (const RV &rvlin, const RV &rvpf, mpdf &par0, mpdf &obs0, int n, const BM_T &BMcond0)
 Default constructor.
void bayes (const vec &dt)
 Incremental Bayes rule.
const epdf_epdf () const
 Returns a pointer to the epdf representing posterior density on parameters. Use with care!
void set_est (const epdf &epdf0)
 Set postrior of rvc to samples from epdf0. Statistics of Bms are not re-computed! Use only for initialization!
virtual void bayesB (const mat &Dt)
 Batch Bayes rule (columns of Dt are observations).
virtual double logpred (const vec &dt) const
const RV_rv () const
 access function
double _ll () const
 access function
void set_evalll (bool evl0)
 access function
virtual BM_copy_ (bool changerv=false)

Public Attributes

double SSAT

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.

Classes

class  mpfepdf
 internal class for MPDF providing composition of eEmp with external components


Detailed Description

template<class BM_T>
class MPF< BM_T >

Marginalized Particle filter.

Trivial version: proposal = parameter evolution, observation model is not used. (it is assumed to be part of BM).


Member Function Documentation

template<class BM_T>
void MPF< BM_T >::bayes ( const vec &  dt  )  [inline, virtual]

Incremental Bayes rule.

Parameters:
dt vector of input data

Reimplemented from PF.

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

virtual double 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 ARX, MixEF, and multiBM.

virtual BM* 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 ARX.

Referenced by MixEF::MixEF().


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

Generated on Tue Sep 23 16:00:54 2008 for mixpp by  doxygen 1.5.6