[384] | 1 | #include "stat/exp_family.h" |
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| 2 | #include "stat/mixtures.h" |
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[254] | 3 | using namespace bdm; |
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[193] | 4 | |
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| 5 | //These lines are needed for use of cout and endl |
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| 6 | using std::cout; |
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| 7 | using std::endl; |
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| 8 | |
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| 9 | double normcoef ( const epdf* ep,const vec &xb, const vec &yb, int Ngr=100 ) { |
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| 10 | mat PPdf ( Ngr+1,Ngr+1 ); |
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| 11 | vec rgr ( 2 ); |
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| 12 | |
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| 13 | int i=0,j=0; |
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| 14 | double xstep= ( xb ( 1 )-xb ( 0 ) ) /Ngr; |
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| 15 | double ystep= ( yb ( 1 )-yb ( 0 ) ) /Ngr; |
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| 16 | |
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| 17 | for ( double x=xb ( 0 );x<=xb ( 1 );x+= xstep,i++ ) { |
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| 18 | rgr ( 0 ) =x;j=0; |
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| 19 | for ( double y=yb ( 0 );y<=yb ( 1 );y+=ystep,j++ ) { |
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| 20 | rgr ( 1 ) =y; |
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[211] | 21 | PPdf ( i,j ) =exp ( ep->evallog ( rgr ) ); |
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[193] | 22 | } |
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| 23 | } |
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| 24 | return sumsum ( PPdf ) *xstep*ystep; |
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| 25 | } |
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| 26 | |
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| 27 | int main() { |
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| 28 | RNG_randomize(); |
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| 29 | |
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| 30 | RV x ( "{x }" ); |
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| 31 | RV y ( "{y }" ); |
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| 32 | RV xy=concat(x,y); |
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| 33 | |
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[270] | 34 | enorm<ldmat> E1; E1.set_rv ( xy ); |
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[193] | 35 | |
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| 36 | it_file iti("xxx"); |
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| 37 | mat R; vec mu; |
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| 38 | iti >> Name("R") >>R; |
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| 39 | iti >> Name("mu") >>mu; |
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| 40 | |
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| 41 | cout << mu << R <<endl; |
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| 42 | E1.set_parameters( mu, R);//"1.00054 1.0455" , mat ( "0.740142 -0.259015; -0.259015 1.0302" )); |
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[270] | 43 | enorm<ldmat> E2;E2.set_rv ( xy ); |
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[193] | 44 | E2.set_parameters( "-1.2 -0.1" , mat ( "1 0.4; 0.4 0.5" )); |
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| 45 | |
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| 46 | Array<epdf*> A1(1); |
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| 47 | A1(0) = &E1; |
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| 48 | |
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[270] | 49 | emix M1; M1.set_rv(xy); |
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[193] | 50 | M1.set_parameters(vec("1"), A1, false); |
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| 51 | cout << "======== test if ARX and emix with one ARX are the same ==="<<endl; |
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| 52 | |
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| 53 | epdf* Mm = M1.marginal(y); |
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| 54 | epdf* Am = E1.marginal(y); |
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| 55 | mpdf* Mc = M1.condition(y); |
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| 56 | mpdf* Ac = E1.condition(y); |
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| 57 | |
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| 58 | cout << *((mlnorm<ldmat>*)Ac) <<endl; |
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| 59 | |
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[211] | 60 | cout << "Mix marg at 0: " << Mm->evallog(vec_1(0.0)) <<endl; |
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| 61 | cout << "ARX marg at 0: " << Am->evallog(vec_1(0.0)) <<endl; |
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| 62 | cout << "Mix cond at 0,0: " << Mc->evallogcond(vec_1(0.0),vec_1(0.0)) <<endl; |
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| 63 | cout << "ARX cond at 0,0: " << Ac->evallogcond(vec_1(0.0),vec_1(0.0)) <<endl; |
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[193] | 64 | |
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| 65 | cout << "======== Mixture with two components ==="<<endl; |
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| 66 | Array<epdf*> A2(2); |
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| 67 | A2(0) = &E1; |
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| 68 | A2(1) = &E2; |
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| 69 | |
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[270] | 70 | emix M2; M2.set_rv(xy); |
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[193] | 71 | M2.set_parameters(vec("1"), A2, false); |
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| 72 | |
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| 73 | |
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| 74 | cout << "Mixture normalization: " << normcoef(&M2, vec("-3 3 "), vec("-3 3 ")) <<endl; |
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| 75 | |
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| 76 | int N=3; |
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| 77 | vec ll ( N ); |
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| 78 | vec ll2 ( N ); |
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[201] | 79 | mat Smp=M2.sample_m ( N ); |
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[211] | 80 | ll = M2.evallog_m(Smp); |
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[193] | 81 | |
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| 82 | vec Emu = sum ( Smp,2 ) /N; |
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| 83 | mat Er = ( Smp*Smp.transpose() ) /N - outer_product ( Emu,Emu ); |
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| 84 | |
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| 85 | cout << "original empirical mean: " <<Emu <<endl; |
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| 86 | cout << "original empirical variance: " <<Er <<endl; |
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| 87 | |
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| 88 | epdf* Mg = (epdf*)M2.marginal ( y ); |
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| 89 | mpdf* Cn = (mpdf*)M2.condition ( x ); |
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| 90 | |
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| 91 | it_file it("emix_test.it"); |
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| 92 | it << Name("Smp") << Smp; |
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| 93 | |
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| 94 | cout<< "marginal mean: " << Mg->mean() <<endl; |
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| 95 | |
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| 96 | cout << "========== putting them back together ======= "<<endl; |
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[203] | 97 | mepdf mMg ( Mg ); |
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[193] | 98 | Array<mpdf*> AA ( 2 ); |
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| 99 | AA ( 0 ) = Cn; |
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| 100 | AA ( 1 ) = &mMg; |
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| 101 | mprod mEp ( AA ); |
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| 102 | |
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| 103 | for (int j=0; j<N; j++){ |
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[211] | 104 | ll2(j)=mEp.evallogcond (Smp.get_col(j), vec ( 0 )); |
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[193] | 105 | } |
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| 106 | it << Name("ll") << ll; |
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| 107 | it << Name("ll2") << ll2; |
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| 108 | |
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| 109 | |
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| 110 | } |
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