# EKFfixed Class Reference

`#include <ekf_obj.h>`

Inheritance diagram for EKFfixed:

List of all members.

## Detailed Description

Extended Kalman Filter with full matrices in fixed point arithmetic.

An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.

## 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
RV | rvc
| Name of extension variable.
const RV & | _rvc () const
| access function
## Logging of results
ivec | LIDs
| IDs of storages in loggers.
bool | opt_L_bounds
| Option for logging bounds.
void | set_options (const string &opt)
| Set boolean options from a string.
void | log_add (logger *L, const string &name="")
| Add all logged variables to a logger.
void | logit (logger *L)
## Public Member Functions
void | init_ekf (double Tv)
void | ekf (double ux, double uy, double isxd, double isyd)
void | prediction (int *ux)
void | correction (void)
void | update_psi (void)
| EKFfixed ()
| Default constructor.
void | bayes (const vec &dt)
| Here dt = [yt;ut] of appropriate dimensions.
epdf & | posterior ()
| dummy!
void | condition (const vec &Q0)
| Substitute `val` for `rvc`.
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 epdf * | epredictor () const
| Constructs a predictive density .
virtual mpdf * | predictor () 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)
virtual const epdf & | posterior () const =0
virtual const epdf * | _e () const =0
## Public Attributes
int | Q [16]
int | R [4]
int | x_est [4]
int | x_pred [4]
int | P_pred [16]
int | P_est [16]
int | Y_mes [2]
int | ukalm [2]
int | Kalm [8]
int | PSI [16]
int | temp15a [16]
int | cA
int | cB
int | cC
int | cG
int | cH
long | temp30a [4]
enorm< fsqmat > | E
mat | Ry
## Protected Attributes
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.

## 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 >, and bdm::EKFCh.

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:

- ekf_obj.h
- ekf_obj.cpp