prepare structure for R package

[valse.git] / R / initSmallEM.R

diff --git a/R/initSmallEM.R b/R/initSmallEM.R
new file mode 100644 (file)
index 0000000..8f3c86b
--- /dev/null
+++ b/R/initSmallEM.R
@@ -0,0 +1,80 @@
+library(MASS) #generalized inverse of matrix Monroe-Penrose
+
+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))
+}
+
+initSmallEM = function(k,X,Y,tau){
+  n = nrow(Y)
+  m = ncol(Y)
+  p = ncol(X)
+
+  betaInit1 = array(0, dim=c(p,m,k,20))
+  sigmaInit1 = array(0, dim = c(m,m,k,20))
+  phiInit1 = array(0, dim = c(p,m,k,20))
+  rhoInit1 = array(0, dim = c(m,m,k,20))
+  piInit1 = matrix(0,20,k)
+  gamInit1 = array(0, dim=c(n,k,20))
+  LLFinit1 = list()
+  
+  
+  for(repet in 1:20){
+    clusters = hclust(dist(y)) #default distance : euclidean
+    clusterCut = cutree(clusters,k)
+    Zinit1[,repet] = clusterCut #retourne les indices (à quel cluster indiv_i appartient) d'un clustering hierarchique (nb de cluster = k)
+    
+    for(r in 1:k){
+      Z = Zinit1[,repet]
+      Z_bin = vec_bin(Z,r)
+      Z_vec = Z_bin[[1]] #vecteur 0 et 1 aux endroits où Z==r
+      Z_indice = Z_bin[[2]] #renvoit les indices où Z==r
+      
+      betaInit1[,,r,repet] = ginv(t(x[Z_indice,])%*%x[Z_indice,])%*%t(x[Z_indice,])%*%y[Z_indice,]
+      sigmaInit1[,,r,repet] = diag(m)
+      phiInit1[,,r,repet] = betaInit1[,,r,repet]/sigmaInit1[,,r,repet]
+      rhoInit1[,,r,repet] = solve(sigmaInit1[,,r,repet])
+      piInit1[repet,r] = sum(Z_vec)/n
+    }
+    
+    for(i in 1:n){
+      for(r in 1:k){
+        dotProduct = (y[i,]%*%rhoInit1[,,r,repet]-x[i,]%*%phiInit1[,,r,repet]) %*% (y[i,]%*%rhoInit1[,,r,repet]-x[i,]%*%phiInit1[,,r,repet])
+        Gam[i,r] = piInit1[repet,r]*det(rhoInit1[,,r,repet])*exp(-0.5*dotProduct)
+      }
+      sumGamI = sum(gam[i,])
+      gamInit1[i,,repet]= Gam[i,] / sumGamI
+    }
+    
+    miniInit = 10
+    maxiInit = 11
+    
+    new_EMG = EMGLLF(phiInit1[,,,repet],rhoInit1[,,,repet],piInit1[repet,],gamInit1[,,repet],miniInit,maxiInit,1,0,x,y,tau)
+    ##.C("EMGLLF", phiInit = phiInit, rhoInit = rhoInit, ...)
+    LLFEessai = new_EMG[[4]]
+    LLFinit1[[repet]] = LLFEessai[[length(LLFEessai)]]
+  }
+  
+  b = which.max(LLFinit1)
+  
+  phiInit = phiInit1[,,,b]
+  rhoInit = rhoInit1[,,,b]
+  piInit = piInit1[b,]
+  gamInit = gamInit1[,,b]
+  
+  return(list(phiInit, rhoInit, piInit, gamInit))
+}
+
+