diff options
Diffstat (limited to 'src')
| -rw-r--r-- | src/projet.cpp | 59 |
1 files changed, 36 insertions, 23 deletions
diff --git a/src/projet.cpp b/src/projet.cpp index 9d3ac15..205e362 100644 --- a/src/projet.cpp +++ b/src/projet.cpp @@ -75,24 +75,37 @@ std::vector<double> normalize (std::vector<double> mu) { } - void exemple2_stratified (int d){ + vector <vector<double> > exemple2_stratified (int d){ std::vector<double> mu(d); - mu = argmax(0.05, 1.0, 50, 0.1, 45, d); - std::vector<double> u(d); - u = normalize(mu); - vector<double> q = quantile_norm(100, 1); - vector<double> p(100, 0.01); - asian_option A(0.05, 1.0, 50, 0.1, 45, true); - exponential_tilt<asian_option> G(mu, A); - typedef compose_t<exponential_tilt<asian_option>, multi_gaussian_truncated> tilted_option; - std::vector<tilted_option> X; - X.push_back(compose(G, multi_gaussian_truncated(GSL_NEGINF,q[0], u))); - for(int i=1; i<100; i++) { - X.push_back(compose(G, multi_gaussian_truncated(q[i-1],q[i], u))); - } - stratified_sampling<tilted_option> S(p, X); - S.draw(1000000); - cout<<"l'estimateur de la moyenne est :"<<S.estimator().first<<endl; + vector<int> K = {45, 50, 55}; + vector<int> N = {100000, 400000, 500000}; + vector< vector<double> > data(3); + for (int i=0; i<3; i++){ + mu = argmax(0.05, 1.0, 50, 0.1, K[i], d); + std::vector<double> u(d); + u = normalize(mu); + vector<double> q = quantile_norm(100, 1); + vector<double> p(100, 0.01); + asian_option A(0.05, 1.0, 50, 0.1, K[i], true); + exponential_tilt<asian_option> G(mu, A); + typedef compose_t<exponential_tilt<asian_option>, multi_gaussian_truncated> tilted_option; + std::vector<tilted_option> X; + X.push_back(compose(G, multi_gaussian_truncated(GSL_NEGINF,q[0], u))); + for(int j=1; j<100; i++) { + X.push_back(compose(G, multi_gaussian_truncated(q[j-1],q[j], u))); + } + stratified_sampling<tilted_option> S(p, X); + vector<double> r(3, 0); + for (int j=0; j<3; i++){ + S.draw(N[j]); + } + r[0] = K[i]; + r[1] = S.estimator().first; + r[2] = S.estimator().second; + data[i] = r; + for(int j=0; i<3; i++){cout<<data[i][j]<<endl;}; + } + return data; } void exemple2_rqmc(int d) { @@ -131,12 +144,12 @@ int make_table1(vector< vector<double> > data1, vector< vector<double> > data2) int main() { init_alea(1); - cout<<gsl_cdf_gaussian_Pinv(0.975,1)<<endl; - cout<<"Stratified_sampling sur l'exemple 1 de la normale"<<endl; - vector< vector<double> > data1 = exemple1_stratified(); - cout<<"Randomised quasi Monte-Carlo sur l'exemple 1 de la normale"<<endl; - vector< vector<double> > data2 = exemple1_rqmc(); - make_table1(data1, data2); + //~ cout<<gsl_cdf_gaussian_Pinv(0.975,1)<<endl; + //~ cout<<"Stratified_sampling sur l'exemple 1 de la normale"<<endl; + //~ vector< vector<double> > data1 = exemple1_stratified(); + //~ cout<<"Randomised quasi Monte-Carlo sur l'exemple 1 de la normale"<<endl; + //~ vector< vector<double> > data2 = exemple1_rqmc(); + //~ make_table1(data1, data2); exemple2_stratified(16); return 0; |