From: emilie <emilie@devijver.org>
Date: Tue, 6 Dec 2016 12:29:09 +0000 (+0100)
Subject: données simulées
X-Git-Url: https://git.auder.net/variants/current/doc/css/img/pieces/index.css?a=commitdiff_plain;h=0b216f854a21821f9be375d07c2932b31e227e78;p=valse.git

données simulées
---

diff --git a/R/generateIO.R b/R/generateIO.R
index 0e776d0..4527f08 100644
--- a/R/generateIO.R
+++ b/R/generateIO.R
@@ -16,16 +16,18 @@ generateIO = function(covX, covY, pi, beta, n)
   k = dim(covY)[3]
   
   Y = matrix(0,n,m)
-  BX = array(0, dim=c(n,m,k))
+  require(mvtnorm)
+  X = rmvnorm(n, mean = rep(0,p), sigma = covX)
   
   require(MASS) #simulate from a multivariate normal distribution
   for (i in 1:n)
   {
+    
     for (r in 1:k)
     {
       BXir = rep(0,m)
       for (mm in 1:m)
-        Bxir[[mm]] = X[i,] %*% beta[,mm,r]
+        BXir[mm] = X[i,] %*% beta[,mm,r]
       Y[i,] = Y[i,] + pi[r] * mvrnorm(1,BXir, covY[,,r])
     }
   }
diff --git a/R/generateIOdefault.R b/R/generateIOdefault.R
index 85213cc..3613f2b 100644
--- a/R/generateIOdefault.R
+++ b/R/generateIOdefault.R
@@ -8,11 +8,10 @@
 #-----------------------------------------------------------------------
 generateIOdefault = function(n, p, m, k)
 {
-  covX = array(0, dim=c(p,p,k))
+  covX = diag(p)
   covY = array(0, dim=c(m,m,k))
   for(r in 1:k)
   {
-    covX[,,r] = diag(p)
     covY[,,r] = diag(m)
   }
   
diff --git a/data/TODO b/data/TODO
index c0603b4..a3bb58d 100644
--- a/data/TODO
+++ b/data/TODO
@@ -1,2 +1,4 @@
 Trouver un jeu de données (+) intéressant (que les autres) ?
 Ajouter toy datasets pour les tests (ou piocher dans MASS ?)
+
+ED : j'ai simulé un truc basique via 'generateIOdefault(10,5,6,2)'
diff --git a/data/data.RData b/data/data.RData
new file mode 100644
index 0000000..a9f09e1
Binary files /dev/null and b/data/data.RData differ