bdm::MultiModel Class Reference

(Switching) Multiple Model The model runs several models in parallel and evaluates thier weights (fittness). More...

#include <kalman.h>

List of all members.

Public Member Functions

void set_parameters (Array< EKFCh * > A, int pol0=1)
void bayes (const vec &dt)
 Incremental Bayes rule.
const enorm< chmat > * _e () const
const enorm< chmat > & posterior () const
void from_setting (const Setting &set)
 This method arrange instance properties according the data stored in the Setting structure.
virtual string to_string ()
 This method returns a basic info about the current instance.
virtual void to_setting (Setting &set) const
 This method save all the instance properties into the Setting structure.
virtual void validate ()
 This method TODO.
Constructors
virtual BM_copy_ () const
Mathematical operations
virtual void bayesB (const mat &Dt)
 Batch Bayes rule (columns of Dt are observations).
virtual double logpred (const vec &dt) const
vec logpred_m (const mat &dt) const
 Matrix version of logpred.
virtual epdfepredictor () const
 Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $.
virtual mpdfpredictor () const
 Constructs a conditional density 1-step ahead predictor.
Access to attributes
const RV_drv () const
void set_drv (const RV &rv)
void set_rv (const RV &rv)
double _ll () const
void set_evalll (bool evl0)

Protected Attributes

Array< EKFCh * > Models
 List of models between which we switch.
vec w
 vector of model weights
vec _lls
 cache of model lls
int policy
 type of switching policy [1=maximum,2=...]
enorm< chmatest
 internal statistics
RV drv
 Random variable of the data (optional).
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.

Extension to conditional BM

This extension is useful e.g. in Marginalized Particle Filter (bdm::MPF). Alternatively, it can be used for automated connection to DS when the condition is observed

const RV_rvc () const
 access function
virtual void condition (const vec &val)
 Substitute val for rvc.
RV rvc
 Name of extension variable.

Logging of results

virtual void set_options (const string &opt)
 Set boolean options from a string, recognized are: "logbounds,logll".
virtual void log_add (logger &L, const string &name="")
 Add all logged variables to a logger.
virtual void logit (logger &L)
ivec LIDs
 IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].
ivec LFlags
 Flags for logging - same size as LIDs, each entry correspond to the same in LIDs.


Detailed Description

(Switching) Multiple Model The model runs several models in parallel and evaluates thier weights (fittness).

The statistics of the resulting density are merged using (geometric?) combination.

The next step is performed with the new statistics for all models.


Member Function Documentation

virtual BM* bdm::BM::_copy_ (  )  const [inline, virtual, inherited]

Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype:

 BM* _copy_() const {return new BM(*this);} 

Reimplemented in bdm::ARX, bdm::KalmanCh, bdm::EKF< sq_T >, bdm::EKFCh, and bdm::BMEF.

void bdm::MultiModel::bayes ( const vec &  dt  )  [inline, virtual]

Incremental Bayes rule.

Parameters:
dt vector of input data

Implements bdm::BM.

References _lls, est, bdm::enorm< sq_T >::mean(), Models, policy, and w.

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().


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

Generated on Wed Aug 5 00:06:59 2009 for mixpp by  doxygen 1.5.9