update valse.R

[valse.git] / R / initSmallEM.R

diff --git a/R/initSmallEM.R b/R/initSmallEM.R
index e2157b2..399f39f 100644 (file)
--- a/R/initSmallEM.R
+++ b/R/initSmallEM.R
@@ -3,11 +3,12 @@
 #' @param k number of components
 #' @param X matrix of covariates (of size n*p)
 #' @param Y matrix of responses (of size n*m)
-#' @param tau threshold to stop EM algorithm
 #'
 #' @return a list with phiInit, rhoInit, piInit, gamInit
 #' @export
-initSmallEM = function(k,X,Y,tau)
+#' @importFrom methods new
+#' @importFrom stats cutree dist hclust runif
+initSmallEM = function(k,X,Y)
 {
        n = nrow(Y)
        m = ncol(Y)
@@ -34,9 +35,13 @@ initSmallEM = function(k,X,Y,tau)
                {
                        Z = Zinit1[,repet]
                        Z_indice = seq_len(n)[Z == r] #renvoit les indices où Z==r
-                       
+                       if (length(Z_indice) == 1) {
+                         betaInit1[,,r,repet] = ginv(crossprod(t(X[Z_indice,]))) %*%
+                           crossprod(t(X[Z_indice,]), Y[Z_indice,])
+                       } else {
                        betaInit1[,,r,repet] = ginv(crossprod(X[Z_indice,])) %*%
                                crossprod(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])
@@ -58,7 +63,7 @@ initSmallEM = function(k,X,Y,tau)
                maxiInit = 11
                
                new_EMG = .Call("EMGLLF_core",phiInit1[,,,repet],rhoInit1[,,,repet],piInit1[repet,],
-                       gamInit1[,,repet],miniInit,maxiInit,1,0,X,Y,tau)
+                       gamInit1[,,repet],miniInit,maxiInit,1,0,X,Y,1e-4)
                LLFEessai = new_EMG$LLF
                LLFinit1[repet] = LLFEessai[length(LLFEessai)]
        }