X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FinitSmallEM.R;h=937ea734aa427710540b69f75585f75eb6968795;hb=04845e3300b5450629bf1a2c3344d2f9419e91a6;hp=d1ade1cdf8e98c573d3f347b25d69ad3f3e79178;hpb=1b698c1619dbcf5b3a0608dc894d249945d2bce3;p=valse.git

diff --git a/pkg/R/initSmallEM.R b/pkg/R/initSmallEM.R
index d1ade1c..937ea73 100644
--- a/pkg/R/initSmallEM.R
+++ b/pkg/R/initSmallEM.R
@@ -1,4 +1,4 @@
-#' initialization of the EM algorithm 
+#' initialization of the EM algorithm
 #'
 #' @param k number of components
 #' @param X matrix of covariates (of size n*p)
@@ -8,11 +8,11 @@
 #' @export
 #' @importFrom methods new
 #' @importFrom stats cutree dist hclust runif
-initSmallEM <- function(k, X, Y, fast = TRUE)
+initSmallEM <- function(k, X, Y, fast)
 {
-  n <- nrow(Y)
-  m <- ncol(Y)
+  n <- nrow(X)
   p <- ncol(X)
+  m <- ncol(Y)
   nIte <- 20
   Zinit1 <- array(0, dim = c(n, nIte))
   betaInit1 <- array(0, dim = c(p, m, k, nIte))
@@ -34,12 +34,12 @@ initSmallEM <- function(k, X, Y, fast = TRUE)
     for (r in 1:k)
     {
       Z <- Zinit1[, repet]
-      Z_indice <- seq_len(n)[Z == r]  #renvoit les indices où Z==r
+      Z_indice <- seq_len(n)[Z == r]  #renvoit les indices ou Z==r
       if (length(Z_indice) == 1) {
-        betaInit1[, , r, repet] <- MASS::ginv(crossprod(t(X[Z_indice, ]))) %*% 
+        betaInit1[, , r, repet] <- MASS::ginv(crossprod(t(X[Z_indice, ]))) %*%
           crossprod(t(X[Z_indice, ]), Y[Z_indice, ])
       } else {
-        betaInit1[, , r, repet] <- MASS::ginv(crossprod(X[Z_indice, ])) %*% 
+        betaInit1[, , r, repet] <- MASS::ginv(crossprod(X[Z_indice, ])) %*%
           crossprod(X[Z_indice, ], Y[Z_indice, ])
       }
       sigmaInit1[, , r, repet] <- diag(m)
@@ -54,10 +54,11 @@ initSmallEM <- function(k, X, Y, fast = TRUE)
       {
         dotProduct <- tcrossprod(Y[i, ] %*% rhoInit1[, , r, repet]
           - X[i, ] %*% phiInit1[, , r, repet])
-        Gam[i, r] <- piInit1[repet, r]
-          * det(rhoInit1[, , r, repet]) * exp(-0.5 * dotProduct)
+        Gam[i, r] <- piInit1[repet, r] *
+          det(rhoInit1[, , r, repet]) * exp(-0.5 * dotProduct)
       }
       sumGamI <- sum(Gam[i, ])
+      # TODO: next line is a division by zero if dotProduct is big
       gamInit1[i, , repet] <- Gam[i, ]/sumGamI
     }
 
@@ -67,8 +68,7 @@ initSmallEM <- function(k, X, Y, fast = TRUE)
     init_EMG <- EMGLLF(phiInit1[, , , repet], rhoInit1[, , , repet], piInit1[repet, ],
       gamInit1[, , repet], miniInit, maxiInit, gamma = 1, lambda = 0, X, Y,
       eps = 1e-04, fast)
-    LLFEessai <- init_EMG$LLF
-    LLFinit1[repet] <- LLFEessai[length(LLFEessai)]
+    LLFinit1[[repet]] <- init_EMG$llh
   }
   b <- which.min(LLFinit1)
   phiInit <- phiInit1[, , , b]