root/library/tests/tutorial/kalman_simple.cpp @ 1063

#include "estim/kalman.h"
using namespace bdm;

// estimation of AR(0) model
int main() {
        //dimensions
        int dx = 3, dy = 3, du = 1;
        // matrices
        mat A = eye ( dx );
        mat B = zeros ( dx, du );
        mat C = eye ( dx );
        mat D = zeros ( dy, du );
        mat Q = eye ( dx );
        mat R = 0.1 * eye ( dy );
        //prior
        mat P0 = 100 * eye ( dx );
        vec mu0 = zeros ( dx );
        // Estimator
        KalmanCh KF;
        KF.set_parameters ( A, B, C, D,/*covariances*/ Q, R );
        KF.set_statistics ( mu0, P0 );
        KF.validate();
        // Estimation loop
        for ( int i = 0; i < 100; i++ ) {
                KF.bayes ( randn ( dy ), randn ( du ) );
        }
        //print results
        cout << "Posterior estimate of x is: "  << endl;
        cout << "mean: " << KF.posterior().mean() << endl;
        cout << "variance: " << KF.posterior().variance() << endl;
}