| 1 | #include "stat/exp_family.h" |
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| 2 | using namespace bdm; |
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| 3 | |
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| 4 | //These lines are needed for use of cout and endl |
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| 5 | using std::cout; |
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| 6 | using std::endl; |
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| 7 | |
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| 8 | void Test ( const egiw &E ) { |
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| 9 | } |
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| 10 | |
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| 11 | int main() { |
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| 12 | cout << "Testing eGiw(1,1)"<<endl; |
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| 13 | { |
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| 14 | // Setup model |
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| 15 | double mu=1.1; |
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| 16 | double s=0.1; |
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| 17 | |
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| 18 | // TEST 1x1 EGIW |
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| 19 | mat V ( 2,2 ); |
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| 20 | V ( 0,0 ) = pow ( mu,2 ) +s; |
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| 21 | V ( 1,0 ) = mu; |
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| 22 | V ( 0,1 ) = V ( 1,0 ); |
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| 23 | V ( 1,1 ) = 1.0; |
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| 24 | |
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| 25 | double nu=10; |
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| 26 | |
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| 27 | egiw E ( 1,nu*V,nu ); |
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| 28 | cout << "egiw mean value:" << E.mean() <<endl; |
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| 29 | cout << "egiw normalizing constant:" << E.lognc() <<endl; |
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| 30 | |
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| 31 | int n=100; |
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| 32 | vec t_val ( 2 ); |
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| 33 | |
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| 34 | mat pdf ( 2*n,n ); |
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| 35 | vec Mu ( 2*n ); |
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| 36 | vec Si ( n ); |
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| 37 | |
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| 38 | for ( int i=0;i<2*n;i++ ) { |
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| 39 | Mu ( i ) = -2+i* ( 1.0/ ( n ) ) *3.0; |
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| 40 | t_val ( 0 ) = Mu ( i ); |
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| 41 | for ( int j=0;j<n;j++ ) { |
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| 42 | Si ( j ) = ( j+1 ) * ( 1.0/n ) *2; |
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| 43 | t_val ( 1 ) = Si ( j ); |
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| 44 | |
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| 45 | pdf ( i,j ) =E.evallog ( t_val ); |
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| 46 | } |
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| 47 | } |
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| 48 | |
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| 49 | mat Pdf=exp ( pdf ); |
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| 50 | vec fm=sum ( Pdf,2 ); |
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| 51 | vec fs=sum ( Pdf,1 ); |
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| 52 | cout << "Numerical mean: " << vec_2 ( Mu*fm/sum ( fm ), Si*fs/sum ( fs ) ) <<endl; |
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| 53 | cout << "Numerical integral of pdf: "<<sumsum ( Pdf/n/n*3*2 ) <<endl; |
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| 54 | } |
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| 55 | cout << "Testing Egiw(1,2)"<<endl; |
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| 56 | { |
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| 57 | // Setup model |
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| 58 | double mu=1.1; //unit step parametr |
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| 59 | double b=3.0; // sequence of <1 -1 1 -1...> |
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| 60 | double s=0.1; |
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| 61 | |
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| 62 | |
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| 63 | // TEST 1x1 EGIW |
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| 64 | mat V ( 3,3 ); |
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| 65 | V ( 0,0 ) = pow ( mu,2 ) +pow ( b ,2 ) +s; |
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| 66 | V ( 1,0 ) = mu; |
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| 67 | V ( 2,0 ) = b; |
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| 68 | |
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| 69 | V ( 0,1 ) = V ( 1,0 ); |
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| 70 | V ( 1,1 ) = 1.0; |
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| 71 | V ( 2,1 ) = 0.0; |
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| 72 | |
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| 73 | V ( 0,2 ) = V ( 2,0 ); |
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| 74 | V ( 1,2 ) = V ( 2,1 ); |
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| 75 | V ( 2,2 ) = 1.0; |
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| 76 | |
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| 77 | |
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| 78 | double nu=20; |
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| 79 | |
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| 80 | egiw E ( 1,nu*V,nu ); |
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| 81 | cout << "egiw mean value:" << E.mean() <<endl; |
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| 82 | cout << "egiw normalizing constant:" << E.lognc() <<endl; |
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| 83 | |
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| 84 | int n=100; |
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| 85 | vec t_val ( 3 ); |
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| 86 | |
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| 87 | mat Tmp= zeros ( 2*n,n ); |
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| 88 | |
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| 89 | double summ=0.0; |
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| 90 | for ( int k=0;k<n;k++ ) { // ALL b |
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| 91 | t_val ( 1 ) = 1 + k* ( 1.0/n ) * 4.0; |
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| 92 | for ( int i=0;i<2*n;i++ ) { //ALL mu |
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| 93 | t_val ( 0 ) = -2+i* ( 1.0/ n ) *3.0; |
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| 94 | for ( int j=0;j<n;j++ ) { // All sigma |
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| 95 | t_val ( 2 ) = ( j+1 ) * ( 1.0/n ) *2.0; |
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| 96 | |
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| 97 | Tmp ( i,j ) = E.evallog ( t_val ); |
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| 98 | } |
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| 99 | } |
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| 100 | summ += sumsum ( exp ( Tmp ) ) /n/n/n*3.0*2.0*4.0; |
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| 101 | } |
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| 102 | |
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| 103 | |
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| 104 | cout << "Numerical integral of pdf: "<<summ <<endl; |
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| 105 | } |
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| 106 | |
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| 107 | |
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| 108 | } |
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