estimateur, intervalles de confiances ...

4 files changed, 34 insertions, 19 deletions

diff --git a/main.cpp b/main.cpp
index 8692967..0728976 100644
--- a/main.cpp
+++ b/main.cpp
@@ -31,13 +31,23 @@ int main()
     stratified_sampling<gaussian_truncated> S(p,rvar);
     S.update(100);
     S.draw();
-    for(int i=0;i<10;i++){
-        cout<<S.get_mean()[i]<<endl;
-    }
-    S.update(500);
+    double x = 1.64*S.estimator().second;
+		cout<<"l'estimateur de la moyenne est :"<<S.estimator().first<<endl;
+		cout<<"Son intervalle de confiance à 95% est :"<<"["<<S.estimator().first-(x/10)<<" ,"<<S.estimator().first+(x/10)<<"]"<<endl;
+    S.update(1000);
     S.draw();
-    for(int i=0;i<10;i++){
-        cout<<S.get_mean()[i]<<endl;
-    }
+		x = 1,64*S.estimator().second;
+		cout<<"l'estimateur de la moyenne est :"<<S.estimator().first<<endl;
+		cout<<"Son intervalle de confiance à 95% est :"<<"["<<S.estimator().first-(x/sqrt(1100))<<" ,"<<S.estimator().first+(x/sqrt(1100))<<"]"<<endl;
+		S.update(10000);
+		S.draw();
+		x = 1,64*S.estimator().second;
+		cout<<"l'estimateur de la moyenne est :"<<S.estimator().first<<endl;
+		cout<<"Son intervalle de confiance à 95% est :"<<"["<<S.estimator().first-(x/sqrt(11100))<<" ,"<<S.estimator().first+(x/sqrt(11100))<<"]"<<endl;
+
+    //~ S.draw();
+    //~ for(int i=0;i<10;i++){
+        //~ cout<<S.get_mean()[i]<<endl;
+    //~ }
     return 0;
 }
diff --git a/qmc b/qmc
new file mode 160000
+Subproject 3723be5c65f44ae0d9ea25a9e563163e3e1b044
diff --git a/rtnorm b/rtnorm
new file mode 100644
index 0000000..1e39751
--- /dev/null
+++ b/rtnorm
diff --git a/stratified_sampling.hpp b/stratified_sampling.hpp
index e9e1823..cf857ec 100644
--- a/stratified_sampling.hpp
+++ b/stratified_sampling.hpp
@@ -54,6 +54,7 @@ struct stratified_sampling {
     vector<double> get_mean();
     vector<double> get_var();
     void print_mean();
+    void print_sigma();
     pair<double,double> estimator();
 private:
     vector<double> p;
@@ -97,22 +98,16 @@ void stratified_sampling<L>::update(int Nk) {
         double scal = std::inner_product(p.begin(), p.end(), sigma.begin(), (double) 0);
         for (int i=0; i < I; i++) {
             m[i] = (Nk-I)*p[i]*sigma[i]/scal;
-            std::cout<<m[i]<<std::endl;
+            //std::cout<<m[i]<<std::endl;
         }
     }
-    std::cout<<"M[O] avant mis à jour"<<M[0]<<endl;
     M[0]+=floor(m[0]);
-    std::cout<<"M[0] après"<<M[0]<<endl;
     double current = m[0];
-    int compteur = M[0];
-    for (int i=1; i<I; i++){
+    for (int i=1; i<I-1; i++){
         M[i] += floor(current+m[i]) - floor(current);
         current += m[i];
-        compteur += M[i];
-        cout<<M[i]<<"\t";
     }
-    cout<<endl;
-    cout<<compteur<<endl;
+    M[I-1]+=Nk-I-floor(current); 
 }
 
 template <typename L>
@@ -143,16 +138,26 @@ vector<double> stratified_sampling<L>::get_var() {
 
 template <typename L>
 void stratified_sampling<L>::print_mean() {
-	    for(int i=0;i<10;i++){
+	cout<<"les espérances :"<<endl;
+	    for(int i=0;i<I;i++){
         cout<<mean[i]<<"\t";
 			}
 			cout<<endl;
 };
 
 template <typename L>
+void stratified_sampling<L>::print_sigma() {
+	cout<<"les écarts types :"<<endl;
+	    for(int i=0;i<I;i++){
+        cout<<sqrt(sigma2[i])<<"\t";
+			}
+			cout<<endl;
+};
+
+template <typename L>
 pair<double,double> stratified_sampling<L>::estimator() {
-	double est_mean;
-	double est_std;
+	double est_mean = 0;
+	double est_std = 0;
 	for (int i=0; i<I; i++) {
 		est_mean += mean[i]*p[i];
 		est_std += sqrt(sigma2[i])*p[i];