bdm::EKFCh_dQ Class Reference
Extended Kalman filter in Choleski form with unknown diagonal Q.
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Detailed Description
Extended Kalman filter in Choleski form with unknown diagonal Q.
#include <ekf_template.h>
Public Member Functions | |
| void | condition (const vec &Q0) |
Substitute val for rvc. | |
| BM * | _copy_ () const |
| copy constructor duplicated - calls different set_parameters | |
| void | set_parameters (const shared_ptr< diffbifn > &pfxu, const shared_ptr< diffbifn > &phxu, const chmat Q0, const chmat R0) |
| Set nonlinear functions for mean values and covariance matrices. | |
| void | set_parameters (const mat &A0, const mat &B0, const mat &C0, const mat &D0, const chmat &Q0, const chmat &R0) |
| set parameters for adapt from Kalman | |
| void | bayes (const vec &dt) |
| Here dt = [yt;ut] of appropriate dimensions. | |
| void | from_setting (const Setting &set) |
| load basic elements of Kalman from structure | |
| void | initialize () |
| initialize internal parametetrs | |
| void | set_statistics (const vec &mu0, const mat &P0) |
| void | set_statistics (const vec &mu0, const chmat &P0) |
| const enorm< chmat > & | posterior () const |
| posterior | |
| shared_ptr< epdf > | shared_posterior () |
| shared posterior | |
| void | validate () |
| 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. | |
| int | _dimx () |
| access function | |
| int | _dimy () |
| access function | |
| int | _dimu () |
| access function | |
| const mat & | _A () const |
| access function | |
| const mat & | _B () const |
| access function | |
| const mat & | _C () const |
| access function | |
| const mat & | _D () const |
| access function | |
| const chmat & | _Q () const |
| access function | |
| const chmat & | _R () const |
| access function | |
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 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 | |
| shared_ptr< diffbifn > | pfxu |
| Internal Model f(x,u). | |
| shared_ptr< diffbifn > | phxu |
| Observation Model h(x,u). | |
| RV | yrv |
| id of output | |
| RV | urv |
| id of input | |
| mat | _K |
| Kalman gain. | |
| shared_ptr< enorm< chmat > > | est |
| posterior | |
| enorm< chmat > | fy |
| marginal on data f(y|y) | |
| 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. | |
| int | dimx |
| cache of rv.count() | |
| int | dimy |
| cache of rvy.count() | |
| int | dimu |
| cache of rvu.count() | |
| mat | A |
| Matrix A. | |
| mat | B |
| Matrix B. | |
| mat | C |
| Matrix C. | |
| mat | D |
| Matrix D. | |
| chmat | Q |
| Matrix Q in square-root form. | |
| chmat | R |
| Matrix R in square-root form. | |
Internal storage - needs initialize() | |
| mat | preA |
| mat | postA |
| post array (triangular matrix) | |
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 | |
| 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. | |
Member Function Documentation
| 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.
References bdm_error.
Referenced by bdm::BM::logpred_m().
The documentation for this class was generated from the following file:
