X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=R%2FbasicInitParameters.R;fp=R%2FbasicInitParameters.R;h=0000000000000000000000000000000000000000;hp=3583e6829ab721e14b43ab1be4687635a55ec0db;hb=ef67d338c7f28ba041abe40ca9a8ab69f8365a90;hpb=c3bc47052f3ccb659659c59a82e9a99ea842398d

diff --git a/R/basicInitParameters.R b/R/basicInitParameters.R
deleted file mode 100644
index 3583e68..0000000
--- a/R/basicInitParameters.R
+++ /dev/null
@@ -1,28 +0,0 @@
-#-----------------------------------------------------------------------
-#' 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))
-
-	piInit = (1./k)*rep.int(1,k)
-
-	rhoInit = array(0, dim=c(m,m,k))
-	for(i in 1:k)
-		rhoInit[,,i] = diag(m)
-
-	gamInit = 0.1*array(1, dim=c(n,k))
-	R = sample(1:k,n, replace=TRUE)
-	for(i in 1:n)
-		gamInit[i,R[i]] = 0.9
-	gamInit = gamInit/sum(gamInit[1,])
-
-	return (data = list(phiInit = phiInit, rhoInit = rhoInit, piInit = piInit, gamInit = gamInit))
-}