R/basicInitParameters.R

   1 #-----------------------------------------------------------------------
   2 #' Initialize the parameters in a basic way (zero for the conditional mean,
   3 #'  uniform for weights, identity for covariance matrices, and uniformly distributed forthe clustering)
   4 #' @param n sample size
   5 #' @param p number of covariates
   6 #' @param m size of the response
   7 #' @param k number of clusters
   8 #' @return list with phiInit, rhoInit,piInit,gamInit
   9 #' @export
  10 #-----------------------------------------------------------------------
  11 basic_Init_Parameters = function(n,p,m,k)
  12 {
  13     phiInit = array(0, dim=c(p,m,k))
  14
  15     piInit = (1./k)*rep.int(1,k)
  16
  17     rhoInit = array(0, dim=c(m,m,k))
  18     for(i in 1:k)
  19         rhoInit[,,i] = diag(m)
  20
  21     gamInit = 0.1*array(1, dim=c(n,k))
  22     R = sample(1:k,n, replace=TRUE)
  23     for(i in 1:n)
  24         gamInit[i,R[i]] = 0.9
  25     gamInit = gamInit/sum(gamInit[1,])
  26
  27     return (data = list(phiInit = phiInit, rhoInit = rhoInit, piInit = piInit, gamInit = gamInit))
  28 }