diff options
| -rw-r--r-- | src/main.cpp | 34 | ||||
| -rw-r--r-- | src/opti.cpp | 3 | ||||
| -rw-r--r-- | src/stratified_sampling.hpp | 9 |
3 files changed, 29 insertions, 17 deletions
diff --git a/src/main.cpp b/src/main.cpp index 561b8c2..fb6df08 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -45,22 +45,36 @@ x = 1.64*S.estimator().second; void exemple2 (){ - std::vector<double> mu(16); - mu = argmax(0.05, 1.0, 50, 0.1, 45, 16); + int d= 16; + std::vector<double> mu(d); + mu = argmax(0.05, 1.0, 50, 0.1, 45, d); double norm_mu = 0; - std::vector<double> u(16); - for(int i=0; i<16; i++) { + std::vector<double> u(d); + for(int i=0; i<d; i++) { norm_mu += mu[i]*mu[i]; - u[i] = mu[i]/norm_mu; + } + for(int i=0; i<d; i++) { + u[i] = mu[i]/sqrt(norm_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, 16); + asian_option A(0.05, 1.0, 50, 0.1, d, 45); f_mu G(mu,A); - multi_gaussian_truncated MG(q[50],q[51], u); - for(int i=0; i<10; i++){ - std::cout<<G(MG())<<std::endl; - } + std::vector<compose_t <f_mu, multi_gaussian_truncated> > 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))); + } + for(int i=0; i<100; i=i+10){ + std::cout<<X[i]()<<endl; + } + stratified_sampling<compose_t <f_mu, multi_gaussian_truncated> > S(p, X); + S.draw(1000); + cout<<"l'estimateur de la moyenne est :"<<S.estimator().first<<endl; + //~ compose_t <f_mu, multi_gaussian_truncated> X = compose(G,MG); + //~ for(int i=0; i<10; i++){ + //~ std::cout<<X()<<std::endl; + //~ } } diff --git a/src/opti.cpp b/src/opti.cpp index 23ddff3..6b05ecd 100644 --- a/src/opti.cpp +++ b/src/opti.cpp @@ -39,9 +39,6 @@ std::vector<double> argmax(double r, double T, double S0, double V, double K, in std::vector<double> x(d,0); std::vector<double> g(0); - - std::cout<<"valeur au début : "<<f(x, g, ¶ms)<<std::endl; - double maxf; nlopt::result result = opt.optimize(x, maxf); diff --git a/src/stratified_sampling.hpp b/src/stratified_sampling.hpp index 7573ef2..c04369e 100644 --- a/src/stratified_sampling.hpp +++ b/src/stratified_sampling.hpp @@ -141,8 +141,9 @@ void stratified_sampling<L>::draw(int N) { m=0; s=0; for(int j=0;j<M[i];j++){ - m=m+X[i](); - s=s+X[i].current()*X[i].current(); + double temp = X[i](); + m=m+temp; + s=s+temp*temp; } oldmean=mean[i]; mean[i]=(mean[i]*cumM[i]+m)/(cumM[i]+M[i]); @@ -192,8 +193,8 @@ pair<double,double> stratified_sampling<L>::estimator() const { struct f_mu : public std::unary_function<std::vector<double>, double> { f_mu(std::vector<double> mu, asian_option A) : mu(mu), A(A){ - double norm_mu = 0; - for(int i=0; i<16; i++) { + norm_mu = 0; + for(unsigned int i=0; i<mu.size(); i++) { norm_mu += mu[i]*mu[i]; } }; |