+#-----------------------------------------------------------------------
+#' Initialize the parameters in a basic way (zero for the conditional mean,
+#' uniform for weights, identity for covariance matrices, and uniformly distributed forthe clustering)
+#' @param n sample size
+#' @param p number of covariates
+#' @param m size of the response
+#' @param k number of clusters
+#' @return list with phiInit, rhoInit,piInit,gamInit
+#' @export
+#-----------------------------------------------------------------------
basic_Init_Parameters = function(n,p,m,k)
{
phiInit = array(0, dim=c(p,m,k))
gamInit[i,R[i]] = 0.9
gamInit = gamInit/sum(gamInit[1,])
- return (list(phiInit, rhoInit, piInit, gamInit))
+ return (data = list(phiInit = phiInit, rhoInit = rhoInit, piInit = piInit, gamInit = gamInit))
}