# multiBM Class Reference

Estimator for Multinomial density. More...

`#include <libEF.h>`

Inheritance diagram for multiBM:

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Collaboration diagram for multiBM:

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List of all members.

## Public Member Functions
| multiBM (const RV &rv, const vec beta0)
| 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 epdf & | _epdf () const
| Returns a reference to the epdf representing posterior density on parameters.
const eDirich * | _e () const
| Returns a pointer to the epdf representing posterior density on parameters. Use with care!
void | set_parameters (const vec &beta0)
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_ (bool changerv=false)
| Flatten the posterior as if to keep nu0 data.
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 * | 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
## 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 | 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

Estimator for Multinomial density.

## Member Function Documentation

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

Incremental Bayes rule.

Parameters:

  | dt | vector of input data

Reimplemented from BMEF.

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

double 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 BM.

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

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

- work/git/mixpp/bdm/stat/libEF.h