X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FinitSmallEM.R;fp=pkg%2FR%2FinitSmallEM.R;h=7e9cce57b6c2cad973db5dc1f794ac764857b7d4;hp=179822fd0b9193d15c15c4ae3389aa25ed63fef4;hb=f32535f2bc8d50470aa87204bbd7971805dbc9ef;hpb=7fd371e5317f9c61fe5a32daadbbac1c64b2dd31

diff --git a/pkg/R/initSmallEM.R b/pkg/R/initSmallEM.R
index 179822f..7e9cce5 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)
@@ -36,10 +36,10 @@ initSmallEM <- function(k, X, Y, fast)
       Z <- Zinit1[, repet]
       Z_indice <- seq_len(n)[Z == r]  #renvoit les indices où 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)
       {
         dotProduct <- tcrossprod(Y[i, ] %*% rhoInit1[, , r, repet]
           - X[i, ] %*% phiInit1[, , r, repet])
-        Gam[i, r] <- piInit1[repet, r] * 
+        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
     }