#include <libPF.h>
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 epdf * | predictor (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 | |
mpdf & | par |
Parameter evolution model. | |
mpdf & | obs |
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. |
Posterior density is represented by a weighted empirical density (eEmp
).
void bdm::PF::bayes | ( | const vec & | dt | ) | [virtual] |
Incremental Bayes rule.
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] |