diff --git a/Comparaison_of_methods.rmd b/Comparaison_of_methods.rmd
index 92e04d0..9c0fabd 100644
--- a/Comparaison_of_methods.rmd
+++ b/Comparaison_of_methods.rmd
@@ -356,24 +356,25 @@ plot_graph_distrib_score(distrib_score_theo, distrib_score_mc)
 ### 3.2. Local score calculation
 ```{r}
 LocalScoreMC <- function(lambda0, lambda1, NbSeq, T, X_seq, P_X, tbe0){
-  E = ComputeE(lambda0, lambda1)
-  
-  pvalue = c()
-  X = c()
-  
-  min_X = min(X_seq)
-  max_X = max(X_seq)
-  
-  for (i in 1:NbSeq){
-      x = floor(E*log(dexp(tbe0[[i]], rate = lambda1)/dexp(tbe0[[i]], rate = lambda0)))
-      LS = localScoreC(x)$localScore[1]
-      
-      daudin_result = daudin(localScore = LS, score_probabilities = P_X, sequence_length = length(x), sequence_min = min_X, sequence_max = max_X)
-      options(warn = -1) # Disable warnings print
-      
-      pvalue = c(pvalue, daudin_result)
+    E = ComputeE(lambda0, lambda1)
+    pvalue = c()
+    X = c()
+    min_X = min(X_seq)
+    max_X = max(X_seq)
+    NbSeq.NonNulles = 0
+    for (i in 1:NbSeq){
+        x = floor(E*log(dexp(tbe0[[i]], rate = lambda1)/dexp(tbe0[[i]], rate = lambda0)))
+        if (length(x)!=0){
+            X = c(X,x)
+            LS = localScoreC(x)$localScore[1]
+            daudin_result = daudin(localScore = LS, score_probabilities = P_X, sequence_length = length(x), sequence_min = min_X, sequence_max = max_X)
+            options(warn = -1) # Disable warnings print
+            pvalue = c(pvalue, daudin_result)
+            NbSeq.NonNulles = NbSeq.NonNulles + 1
+
+        }
   }
-  LS_H0=data.frame(num=1:NbSeq, pvalue_scan=pvalue, class=as.numeric(pvalue<0.05))
+  LS_H0=data.frame(num=1:NbSeq.NonNulles, pvalue_scan=pvalue, class=(pvalue<0.05)*1)
   return(LS_H0)
 }
 ```
@@ -451,20 +452,16 @@ CompareMethods <- function(lambda0, lambda1, NbSeq, T, tau){
 ```
 
 ```{r}
-NbSeq = 10**2
+NbSeq = 10**4
 T = 10
 tau = 2
 
 list_of_lambda = list()
 list_of_lambda[[1]] = c(1, 3)
-list_of_lambda[[2]] = c(1, 4)
-list_of_lambda[[3]] = c(1, 5)
-list_of_lambda[[4]] = c(2, 4)
-list_of_lambda[[5]] = c(2, 5)
-list_of_lambda[[6]] = c(2, 6)
-list_of_lambda[[7]] = c(4, 5)
-list_of_lambda[[8]] = c(4, 8)
-list_of_lambda[[9]] = c(4, 10)
+list_of_lambda[[2]] = c(2, 6)
+list_of_lambda[[3]] = c(4, 7)
+list_of_lambda[[4]] = c(2, 9)
+
 
 i = 1
 legend_list = c()