KalmanCh Kalman< chmat > EKFCh libKF.h mat mat KalmanCh::preA preA pre array (triangular matrix) EKFCh::bayes bayes EKF_unQ::condition EKFCh::set_parameters set_parameters mat mat KalmanCh::postA postA post array (triangular matrix) EKFCh::bayes bayes RV RV Kalman< chmat >::rvy rvy Indetifier of output rv. RV RV Kalman< chmat >::rvu rvu Indetifier of exogeneous rv. int int Kalman< chmat >::dimx dimx cache of rv.count() EKFCh::bayes bayes EKF_unQ::condition EKFCh::set_parameters set_parameters int int Kalman< chmat >::dimy dimy cache of rvy.count() EKFCh::bayes bayes EKF_unQ::condition EKFCh::set_parameters set_parameters int int Kalman< chmat >::dimu dimu cache of rvu.count() EKFCh::bayes bayes EKFCh::set_parameters mat mat Kalman< chmat >::A A Matrix A. EKFCh::bayes bayes EKFCh::set_parameters mat mat Kalman< chmat >::B B Matrix B. bayes EKFCh::set_parameters mat mat Kalman< chmat >::C C Matrix C. EKFCh::bayes bayes EKFCh::set_parameters mat mat Kalman< chmat >::D D Matrix D. bayes EKFCh::set_parameters chmat chmat Kalman< chmat >::Q Q Matrix Q in square-root form. EKF_unQ::condition EKFCh::set_parameters set_parameters chmat chmat Kalman< chmat >::R R Matrix R in square-root form. EKFCh::set_parameters set_parameters enorm< chmat > enorm<chmat > Kalman< chmat >::est est posterior density on $x_t$ set_est enorm< chmat > enorm<chmat > Kalman< chmat >::fy fy preditive density on $y_t$ EKFCh::bayes bayes mat mat Kalman< chmat >::_K _K placeholder for Kalman gain EKFCh::bayes bayes vec & vec& Kalman< chmat >::_yp _yp cache of fy.mu EKFCh::bayes bayes chmat & chmat & Kalman< chmat >::_Ry _Ry cache of fy.R EKFCh::bayes bayes vec & vec& Kalman< chmat >::_mu _mu cache of est.mu EKFCh::bayes bayes EKFCh::set_parameters chmat & chmat & Kalman< chmat >::_P _P cache of est.R EKFCh::bayes bayes RV RV BM::rv rv Random variable of the posterior. BM::_rv MPF< BM_T >::MPF EKFfull::set_parameters ARX::structure_est double double BM::ll ll Logarithm of marginalized data likelihood. BM::_ll EKFfixed::bayes EKF< sq_T >::bayes Kalman< sq_T >::bayes EKFCh::bayes bayes EKFfull::bayes ARX::bayes bool bool BM::evalll 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 time. EKFfixed::bayes EKF< sq_T >::bayes Kalman< sq_T >::bayes EKFCh::bayes bayes EKFfull::bayes ARX::bayes KalmanCh::KalmanCh (RV rvx0, RV rvy0, RV rvu0) KalmanCh RV rvx0 RV rvy0 RV rvu0 Default constructor. void void KalmanCh::set_parameters (const mat &A0, const mat &B0, const mat &C0, const mat &D0, const chmat &R0, const chmat &Q0) set_parameters set_parameters const mat & A0 const mat & B0 const mat & C0 const mat & D0 const chmat & R0 const chmat & Q0 Set parameters with check of relevance. chmat::_Ch Kalman< chmat >::dimx Kalman< chmat >::dimy preA Kalman< chmat >::Q Kalman< chmat >::R void void KalmanCh::set_est (const vec &mu0, const chmat &P0) set_est set_est const vec & mu0 const chmat & P0 Set estimate values, used e.g. in initialization. Kalman< chmat >::est enorm< sq_T >::set_parameters void void KalmanCh::bayes (const vec &dt) bayes bayes bayes const vec & dt Here dt = [yt;ut] of appropriate dimensions. The following equality hold::\[ \left[\begin{array}{cc} R^{0.5}\\ P_{t|t-1}^{0.5}C' & P_{t|t-1}^{0.5}CA'\\ & Q^{0.5}\end{array}\right]<\mathrm{orth.oper.}>=\left[\begin{array}{cc} R_{y}^{0.5} & KA'\\ & P_{t+1|t}^{0.5}\\ \\\end{array}\right]\]Thus this object evaluates only predictors! Not filtering densities. chmat::_Ch Kalman< chmat >::_K Kalman< chmat >::_mu Kalman< chmat >::_P Kalman< chmat >::_Ry Kalman< chmat >::_yp Kalman< chmat >::A Kalman< chmat >::B Kalman< chmat >::C Kalman< chmat >::D Kalman< chmat >::dimu Kalman< chmat >::dimx Kalman< chmat >::dimy BM::evalll enorm< sq_T >::evalpdflog Kalman< chmat >::fy BM::ll postA preA chmat::to_mat void void BM::bayes (mat Dt) bayes mat Dt Batch Bayes rule (columns of Dt are observations). epdf & epdf& Kalman< chmat >::_epdf () _epdf _epdf access function mat & mat& Kalman< chmat >::__K () __K access function vec vec Kalman< chmat >::_dP () _dP access function const RV & const RV& BM::_rv () const _rv access function BM::rv double double BM::_ll () const _ll access function BM::ll Kalman filter in square root form. EKFCh BM EKF_unQ KalmanCh Kalman< chmat > < chmat > Kalman< sq_T > enorm< sq_T > R sq_T epdf rv BM rv RV sqmat KalmanCh Kalman< chmat > _P Q R _Ry rvu rvy est fy < chmat > enorm< chmat > R < chmat > Kalman< sq_T > _P Q R _Ry rvu rvy chmat eEF KalmanCh__K KalmanCh_dP KalmanCh_epdf KalmanCh_K KalmanCh_ll KalmanCh_mu KalmanCh_P KalmanCh_rv KalmanCh_Ry KalmanCh_yp KalmanChA KalmanChB KalmanChbayes KalmanChbayes KalmanChBM KalmanChC KalmanChD KalmanChdimu KalmanChdimx KalmanChdimy KalmanChest KalmanChevalll KalmanChfy KalmanChKalman KalmanChKalman KalmanChKalmanCh KalmanChll KalmanChpostA KalmanChpreA KalmanChQ KalmanChR KalmanChrv KalmanChrvu KalmanChrvy KalmanChset_est KalmanChset_parameters KalmanCh~BM