From d4c688774073c75d2085854627568343b4f959ab Mon Sep 17 00:00:00 2001
From: Bertrand <bertrand.horel@gmail.com>
Date: Thu, 21 Apr 2016 13:53:46 +0200
Subject: début maketable2
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---
 doc/rapport.bib | 12 ++++++++++++
 doc/rapport.tex |  1 +
 src/projet.cpp  | 30 +++++++++++++++++++++++++++---
 3 files changed, 40 insertions(+), 3 deletions(-)

diff --git a/doc/rapport.bib b/doc/rapport.bib
index 3ff0dc5..029824a 100644
--- a/doc/rapport.bib
+++ b/doc/rapport.bib
@@ -45,3 +45,15 @@
  address = {New York, NY, USA},
  keywords = {Monte Carlo, antithetic variates, low discrepancy sequences, product-form networks, variance reduction},
 } 
+
+@article{glasserman1999asymptotically,
+  title={Asymptotically Optimal Importance Sampling and Stratification for Pricing Path-Dependent Options},
+  author={Glasserman, Paul and Heidelberger, Philip and Shahabuddin, Perwez},
+  journal={Mathematical finance},
+  volume={9},
+  number={2},
+  pages={117--152},
+  year={1999},
+  publisher={Wiley Online Library}
+}
+
diff --git a/doc/rapport.tex b/doc/rapport.tex
index 08686c3..c771e1d 100644
--- a/doc/rapport.tex
+++ b/doc/rapport.tex
@@ -240,6 +240,7 @@ $\mathbb{R}$ en $I=100$ strates suivant les quantiles au $1/100^{\textrm{ème}}$
 technique utile dans ce cas car on ne connait pas la suite des $\sigma_i = \mathrm{Var}(f_{\mu}(X)|u'X\in [y_{i-1},y_i])$.
 
 
+
 \printbibliography
 
 \end{document}
diff --git a/src/projet.cpp b/src/projet.cpp
index 46952e2..85f56ab 100644
--- a/src/projet.cpp
+++ b/src/projet.cpp
@@ -146,7 +146,26 @@ int make_table1(vector< vector<double> > data1, vector< vector<double> > data2)
     return 0;
 }
 
-
+int make_table2(vector< vector<double> > data1, vector< vector<double> > data2, vector< vector<double> > data3, vector< vector<double> > data4) {
+    std::fstream fs("doc/table2.tex", std::fstream::out);
+    fs<<R"(\begin{tabular}{|r|r|rr|rr|c|})"<<std::endl;
+    fs<<R"(\hline)"<<endl;
+    fs<<"d"<<" & "<<"K"<<" & "<<R"($\mu_{strat}$)"<<" & "<<R"($\mu_{rqmc}$)"<<" & "<<R"($\textrm{IC}_{strat}$)"<<" & "<<R"($\textrm{IC}_{rqmc}$)"<<" & "<< R"($\textrm{IC}_{strat}/\textrm{IC}_{rqmc}$)"<<R"(\\ \hline)"<<std::endl;
+    fs.precision(2);
+    int N = 1000000;
+    for (int i=0; i< 3; i++) {
+        double ic_strat16 = 1.95996*sqrt(data1[i][2]/(double) N);
+        fs<<"16"<<" & "<< (int) (data1[i][0]) << scientific <<"$"<< data1[i][1] <<" & "<<data2[i][0]<<" & "<<ic_srat16<<" & "<<data2[i][2]/2<<" & "<<fixed<<ic_strat16/(data2[i][2]/2)<<std::endl;
+    }
+    for (int i=0; i< 3; i++) {
+        double ic_strat64 = 1.95996*sqrt(data3[i][2]/(double) N);
+        fs<<"64"<<" & "<< (int) (data3[i][0]) << scientific <<"$"<< data3[i][1] <<" & "<<data4[i][0]<<" & "<<ic_srat64<<" & "<<data4[i][2]/2<<" & "<<fixed<<ic_strat64/(data4[i][2]/2)<<R"(\\ \hline)"<<std::endl;
+    }
+    fs<<R"(\end{tabular})"<<std::endl;
+    fs.close();
+    return 0;
+}
+        
 int main()
 {
     init_alea(2);
@@ -156,8 +175,13 @@ int main()
     //~ cout<<"Randomised quasi Monte-Carlo sur l'exemple 1 de la normale"<<endl;
     //~ vector< vector<double> > data2 = exemple1_rqmc();
     //~ make_table1(data1, data2);
-    exemple2_rqmc(16);
-    exemple2_stratified(16);
+
+    vector< vector<double> > data1 = exemple2_stratified(16);
+    vector< vector<double> > data2 = exemple2_rqmc(16);    
+    vector< vector<double> > data3 = exemple2_stratified(64);
+    vector< vector<double> > data4 = exemple2_rqmc(64); 
+    make_table2(data1, data2, data3, data4);
+    
     return 0;
 
 }
-- 
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