started to look at EMGLLF.c

diff --git a/pkg/R/EMGLLF.R b/pkg/R/EMGLLF.R
index bf4476b..2aeea53 100644 (file)
--- a/pkg/R/EMGLLF.R
+++ b/pkg/R/EMGLLF.R
@@ -19,7 +19,8 @@
 #'   rho : parametre de variance renormalisé, calculé par l'EM
 #'   pi : parametre des proportions renormalisé, calculé par l'EM
 #'   LLF : log vraisemblance associée à cet échantillon, pour les valeurs estimées des paramètres
-#'   S : ... affec : ...
+#'   S : ...
+#'   affec : ...
 #'
 #' @export
 EMGLLF <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda, 
@@ -41,6 +42,7 @@ EMGLLF <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda,
     X, Y, eps, phi = double(p * m * k), rho = double(m * m * k), pi = double(k), 
     LLF = double(maxi), S = double(p * m * k), affec = integer(n), n, p, m, k, 
     PACKAGE = "valse")
+       list(phi = phi, rho = rho, pi = pi, llh = llh, S = S, affec=affec)
 }
 
 # R version - slow but easy to read
@@ -190,5 +192,6 @@ EMGLLF <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda,
       break
   }
 
-  list(phi = phi, rho = rho, pi = pi, llh = llh, S = S)
+       affec = apply(gam, 1, which.max)
+  list(phi = phi, rho = rho, pi = pi, llh = llh, S = S, affec=affec)
 }

diff --git a/pkg/data/script_data.R b/pkg/data/script_data.R
deleted file mode 100644 (file)
index 7479674..0000000
--- a/pkg/data/script_data.R
+++ /dev/null
@@ -1,15 +0,0 @@
-m=6
-p=6
-
-covY = array(0,dim = c(m,m,2))
-covY[,,1] = diag(m)
-covY[,,2] = diag(m)
-
-Beta = array(0, dim = c(p, m, 2))
-Beta[1:4,1:4,1] = 3*diag(4)
-Beta[1:4,1:4,2] = -2*diag(4)
-
-#Data = generateXY(200, c(0.5,0.5), rep(0,p), Beta, diag(p), covY)
-#  
-#Res = valse(Data$X,Data$Y, fast=FALSE, plot=FALSE, verbose = TRUE, kmax=3, size_coll_mod = 50, selecMod = "DDSE", mini = 50, maxi=100)
-#plot(Res$tableau[,3], -Res$tableau[,4])

diff --git a/test/script_data.R b/test/script_data.R
new file mode 100644 (file)
index 0000000..102961c
--- /dev/null
+++ b/test/script_data.R
@@ -0,0 +1,15 @@
+m=6
+p=6
+
+covY = array(0,dim = c(m,m,2))
+covY[,,1] = diag(m)
+covY[,,2] = diag(m)
+
+Beta = array(0, dim = c(p, m, 2))
+Beta[1:4,1:4,1] = 3*diag(4)
+Beta[1:4,1:4,2] = -2*diag(4)
+
+Data = generateXY(200, c(0.5,0.5), rep(0,p), Beta, diag(p), covY)
+#  
+Res = valse(Data$X,Data$Y, fast=FALSE, plot=FALSE, verbose = TRUE, kmax=3, size_coll_mod = 50, selecMod = "DDSE", mini = 50, maxi=100)
+plot(Res$tableau[,3], -Res$tableau[,4])