R/Hierarchical.sim.noise.R

In mosclust: Model Order Selection for Clustering

"Hierarchical.sim.noise" <-
function(X, c = 2, nnoisy=100, perc=0.5, s = sFM, distance="euclidean", hmethod="ward.D") {

 n <- ncol(X);
 sim.vector <- numeric(nnoisy);
 
 for (i in 1:nnoisy)  {
   X1 <- perturb.by.noise(X, perc);	 
	 if (distance == "euclidean")
		  d <- stats::dist (t(X1))
	 else 
			d <- stats::as.dist(1 - stats::cor(X1));
	 tr1 <- stats::hclust(d, method = hmethod);
	 plot(tr1, main="");
	 cl1 <- stats::rect.hclust(tr1, k = c);
	 M1 <- Do.boolean.membership.matrix(cl1, n, 1:n);
	 
	 X2 <- perturb.by.noise(X, perc);	 
	 if (distance == "euclidean")
		  d <- stats::dist(t(X2))
	 else 
			d <- stats::as.dist(1 - stats::cor(X2));
	 tr2 <- stats::hclust(d, method = hmethod);
	 plot(tr2, main="");
	 cl2 <- stats::rect.hclust(tr2, k = c);
	 M2 <- Do.boolean.membership.matrix(cl2, n, 1:n);
	 
	 sim.vector[i] <- s(M1,M2);
 }
 return(sim.vector);
}