root/library/tests/arx_elem_test.cpp @ 384

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

int main() {
        // Setup model : ARX for 1D Gaussian    
        //Test constructor
        mat V0 = 0.00001*eye(2); V0(0,0)= 0.1; //
        ARX Ar; Ar.set_statistics(1, V0, -1.0);
                                
        mat mu(1,1);
        mat R(1,1);
        Ar._e()->mean_mat(mu,R);
        cout << "Prior moments: mu="<< mu << ", R=" << R <<endl; 
        
        int ndat = 200;
        vec smp=randn(ndat);
        //
        mat Smp=ones(2,ndat);
        Smp.set_row(0,smp);
        //
        Ar.bayesB(Smp);
        // Ar is now filled with estimates of N(0,1);
        cout << "Empirical moments: mu=" << sum(smp)/ndat << ", R=" << sum_sqr(smp)/ndat - pow(sum(smp)/ndat,2) << endl;
        Ar._e()->mean_mat(mu,R);
        cout << "Posterior moments: mu="<< mu << ", R=" << R <<endl; 
        
        //////// TEST prediction
        vec x=linspace(-3.0,3.0,100);
        double xstep = 6.0/100.0;
        mat X(1,100);
        mat X2(2,100);
        X.set_row(0,x);
        X2.set_row(0,x);
        
        mlstudent* Ap = Ar.predictor_student();
        vec Ap_x=Ap->evallogcond_m(X,vec_1(1.0));
        vec ll_x = Ar.logpred_m(X2);
        
        cout << "normalize : " << xstep*sum(exp(Ap_x)) << endl;
        cout << "normalize : " << xstep*sum(exp(ll_x)) << endl;
        
        it_file it("arx_elem_test.it");
        it << Name("Ap_x") << Ap_x;
        it << Name("ll_x") << ll_x;
}