# bdm::multiBM Class Reference

Estimator for Multinomial density. More...

`#include <exp_family.h>`

List of all members.

## Public Member Functions
| multiBM ()
| Default constructor.
| multiBM (const multiBM &B)
| Copy constructor.
void | set_statistics (const BM *mB0)
| Sets sufficient statistics to match that of givefrom mB0.
void | bayes (const vec &dt)
| Incremental Bayes rule.
double | logpred (const vec &dt) const
void | flatten (const BMEF *B)
| Flatten the posterior according to the given BMEF (of the same type!).
const eDirich & | posterior () const
| reimplemnetation of BM::posterior()
void | set_parameters (const vec &beta0)
| constructor function
virtual void | set_statistics (const BMEF *BM0)
| get statistics from another model
virtual void | bayes (const vec &data, const double w)
| Weighted update of sufficient statistics (Bayes rule).
BMEF * | _copy_ () const
| Flatten the posterior as if to keep nu0 data.
virtual string | to_string ()
| This method returns a basic info about the current instance.
virtual void | from_setting (const Setting &set)
| This method arrange instance properties according the data stored in the Setting structure.
virtual void | to_setting (Setting &set) const
| This method save all the instance properties into the Setting structure.
virtual void | validate ()
| This method TODO.
Mathematical operations
virtual void | bayesB (const mat &Dt)
| Batch Bayes rule (columns of Dt are observations).
vec | logpred_m (const mat &dt) const
| Matrix version of logpred.
virtual epdf * | epredictor () const
| Constructs a predictive density .
virtual mpdf * | predictor () const
| Constructs conditional density of 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
eDirich | est
| Conjugate prior and posterior.
vec & | beta
| Pointer inside est to sufficient statistics.
double | frg
| forgetting factor
double | last_lognc
| cached value of lognc() in the previous step (used in evaluation of `ll` )
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

Estimator for Multinomial density.

## Member Function Documentation

void bdm::multiBM::bayes | ( | const vec & | dt | ) | `[inline, virtual]`

Incremental Bayes rule.

Parameters:

  | dt | vector of input data

Reimplemented from bdm::BMEF.

References beta, est, bdm::BM::evalll, bdm::BMEF::frg, bdm::BMEF::last_lognc, bdm::BM::ll, and bdm::eDirich::lognc().

double bdm::multiBM::logpred | ( | const vec & | dt | ) | const`[inline, virtual]`

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

Reimplemented from bdm::BM.

References bdm::eDirich::_beta(), beta, est, bdm::BM::evalll, bdm::BMEF::frg, bdm::BMEF::last_lognc, and bdm::eDirich::lognc().

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

- exp_family.h