Folder reorganization

[valse.git] / reports / essai16mars.R

diff --git a/reports/essai16mars.R b/reports/essai16mars.R
new file mode 100644 (file)
index 0000000..d835599
--- /dev/null
+++ b/reports/essai16mars.R
@@ -0,0 +1,88 @@
+meanX = rep(0,6)
+covX = 0.1*diag(6)
+
+covY = array(dim = c(5,5,2))
+covY[,,1] = 0.1*diag(5)
+covY[,,2] = 0.2*diag(5)
+
+beta = array(dim = c(6,5,2))
+beta[,,2] = matrix(c(rep(2,12),rep(0, 18)))
+beta[,,1] = matrix(c(rep(1,12),rep(0, 18)))
+
+n = 500
+
+pi = c(0.4,0.6)
+
+source('~/valse/R/generateSampleInputs.R')
+data = generateXY(meanX,covX,covY, pi, beta, n)
+
+X = data$X
+Y = data$Y
+
+k = 2
+
+n = nrow(Y)
+m = ncol(Y)
+p = ncol(X)
+
+Zinit1 = array(0, dim=c(n))
+betaInit1 = array(0, dim=c(p,m,k))
+sigmaInit1 = array(0, dim = c(m,m,k))
+phiInit1 = array(0, dim = c(p,m,k))
+rhoInit1 = array(0, dim = c(m,m,k))
+Gam = matrix(0, n, k)
+piInit1 = matrix(0,k)
+gamInit1 = array(0, dim=c(n,k))
+LLFinit1 = list()
+
+require(MASS) #Moore-Penrose generalized inverse of matrix
+
+  distance_clus = dist(X)
+  tree_hier = hclust(distance_clus)
+  Zinit1 = cutree(tree_hier, k)
+  sum(Zinit1==1)
+  
+  for(r in 1:k)
+  {
+    Z = Zinit1
+    Z_indice = seq_len(n)[Z == r] #renvoit les indices où Z==r
+    if (length(Z_indice) == 1) {
+      betaInit1[,,r] = ginv(crossprod(t(X[Z_indice,]))) %*%
+        crossprod(t(X[Z_indice,]), Y[Z_indice,])
+    } else {
+      betaInit1[,,r] = ginv(crossprod(X[Z_indice,])) %*%
+        crossprod(X[Z_indice,], Y[Z_indice,])
+    }
+    sigmaInit1[,,r] = diag(m)
+    phiInit1[,,r] = betaInit1[,,r] #/ sigmaInit1[,,r]
+    rhoInit1[,,r] = solve(sigmaInit1[,,r])
+    piInit1[r] = mean(Z == r)
+  }
+  
+  for(i in 1:n)
+  {
+    for(r in 1:k)
+    {
+      dotProduct = tcrossprod(Y[i,]%*%rhoInit1[,,r]-X[i,]%*%phiInit1[,,r])
+      Gam[i,r] = piInit1[r]*det(rhoInit1[,,r])*exp(-0.5*dotProduct)
+    }
+    sumGamI = sum(Gam[i,])
+    gamInit1[i,]= Gam[i,] / sumGamI
+  }
+  
+  miniInit = 10
+  maxiInit = 101
+  
+  new_EMG = EMGLLF(phiInit1,rhoInit1,piInit1,gamInit1,miniInit,maxiInit,1,0,X,Y,1e-6)
+  
+  new_EMG$phi
+  new_EMG$pi
+  LLFEessai = new_EMG$LLF
+  LLFinit1 = LLFEessai[length(LLFEessai)]
+
+
+b = which.max(LLFinit1)
+phiInit = phiInit1[,,,b]
+rhoInit = rhoInit1[,,,b]
+piInit = piInit1[b,]
+gamInit = gamInit1[,,b]