prepare structure for R package

[valse.git] / InputParameters / initSmallEM.R

diff --git a/InputParameters/initSmallEM.R b/InputParameters/initSmallEM.R
deleted file mode 100644 (file)
index 8f3c86b..0000000
--- a/InputParameters/initSmallEM.R
+++ /dev/null
@@ -1,80 +0,0 @@
-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))
-}
-
-