[valse.git] / R / initSmallEM.R

library(MASS) #generalized inverse of matrix Monroe-Penrose

vec_bin = function(X,r){
  Z = c()
  indice = c()
  j=1
  for(i in 1:length(X)){
    if(X[i] == r){
      Z[i] = 1
      indice[j] = i
      j=j+1
    }
    else{
      Z[i] = 0
    }
  }
  return(list(Z,indice))
}

initSmallEM = function(k,X,Y,tau){
  n = nrow(Y)
  m = ncol(Y)
  p = ncol(X)

  betaInit1 = array(0, dim=c(p,m,k,20))
  sigmaInit1 = array(0, dim = c(m,m,k,20))
  phiInit1 = array(0, dim = c(p,m,k,20))
  rhoInit1 = array(0, dim = c(m,m,k,20))
  piInit1 = matrix(0,20,k)
  gamInit1 = array(0, dim=c(n,k,20))
  LLFinit1 = list()
  
  
  for(repet in 1:20){
    clusters = hclust(dist(y)) #default distance : euclidean
    clusterCut = cutree(clusters,k)
Commit	Line	Data
35b42a4b B	1	library(MASS) #generalized inverse of matrix Monroe-Penrose
	2
	3	vec_bin = function(X,r){
	4	Z = c()
	5	indice = c()
	6	j=1
	7	for(i in 1:length(X)){
	8	if(X[i] == r){
	9	Z[i] = 1
	10	indice[j] = i
	11	j=j+1
	12	}
	13	else{
	14	Z[i] = 0
	15	}
	16	}
	17	return(list(Z,indice))
	18	}
	19
	20	initSmallEM = function(k,X,Y,tau){
	21	n = nrow(Y)
	22	m = ncol(Y)
	23	p = ncol(X)
	24
	25	betaInit1 = array(0, dim=c(p,m,k,20))
	26	sigmaInit1 = array(0, dim = c(m,m,k,20))
	27	phiInit1 = array(0, dim = c(p,m,k,20))
	28	rhoInit1 = array(0, dim = c(m,m,k,20))
	29	piInit1 = matrix(0,20,k)
	30	gamInit1 = array(0, dim=c(n,k,20))
	31	LLFinit1 = list()
	32
	33
	34	for(repet in 1:20){
	35	clusters = hclust(dist(y)) #default distance : euclidean
	36	clusterCut = cutree(clusters,k)
	37