R: cosmetics + start translation of (selmix.m into) main.R

[valse.git] / R / selectionmodele.R

diff --git a/R/selectionmodele.R b/R/selectionmodele.R
index b92c4e4..ed32731 100644 (file)
--- a/R/selectionmodele.R
+++ b/R/selectionmodele.R
@@ -1,38 +1,45 @@
-vec_bin = function(X,r){
-  Z = c()
-  indice = c()
-  j=1
-  for(i in 1:length(X)){
-    if(X[i] == r){
-      Z[i] = 1
-      indice[j] = i
-      j=j+1
-    }
-    else{
-      Z[i] = 0
-    }
-  }
-  return(list(Z,indice))
+vec_bin = function(X,r)
+{
+       Z = c()
+       indice = c()
+
+       j = 1
+       for(i in 1:length(X))
+       {
+               if(X[i] == r)
+               {
+                       Z[i] = 1
+                       indice[j] = i
+                       j=j+1
+               } else
+                       Z[i] = 0
+       }
+
+       return (list(Z=Z,indice=indice))
 }
 
-selectionmodele = function(vraisemblance){
-  D = vraimsemblance[,2]
-  D1 = unique(D)
-  
-  indice = rep(1, length(D1))
-  
-  #select argmax MLE
-  if(length(D1)>2){
-    for(i in 1:length(D1)){
-      A = c()
-      for(j in 1:length(D)){
-        if(D[[j]]==D1[[i]]){
-          a = c(a, vraimsemblance[j,1])
-        }
-      }
-      b = max(a)
-      indice[i] = which.max(vec_bin(vraimsemblance,b)[[1]]) #retourne le premier indice du vecteur binaire où u_i ==1
-    }
-  }
-  return(list(indice,D1))
-}
\ No newline at end of file
+selectionmodele = function(vraisemblance)
+{
+       D = vraimsemblance[,2]
+       D1 = unique(D)
+
+       indice = rep(1, length(D1))
+       #select argmax MLE
+       if (length(D1)>2)
+       {
+               for (i in 1:length(D1))
+               {
+                       A = c()
+                       for (j in 1:length(D))
+                       {
+                               if(D[[j]]==D1[[i]])
+                                       a = c(a, vraimsemblance[j,1])
+                       }
+                       b = max(a)
+                       #indice[i] : premier indice du vecteur binaire où u_i ==1
+                       indice[i] = which.max(vec_bin(vraimsemblance,b)[[1]])
+               }
+       }
+
+       return (list(indice=indice,D1=D1))
+}