R/e.cluster.decision.r

In echelon: The Echelon Analysis and the Detection of Spatial Clusters using Echelon Scan Method

########################
### Cluster decision ###
########################

e.cluster.decision <- function(reg_data,log.lambda){
	
	log.lambda2 <- log.lambda[order(log.lambda,decreasing=TRUE)]
	reg_data2 <- reg_data[order(log.lambda,decreasing=TRUE),,drop=FALSE]

	k <- NULL
	cluster_reg <- reg_data2[1,,drop=FALSE]
	
	if(nrow(reg_data2) != 1){
		for(i in 2:nrow(reg_data2)){
			if(any(is.element(cluster_reg[which(!is.na(cluster_reg))],reg_data2[i,][which(!is.na(reg_data2[i,]))]))) k <- c(k,i)
			else cluster_reg <- rbind(cluster_reg,reg_data2[i,])
		}
		if(!is.null(k)) cluster_log.lambda <- log.lambda2[-k]
		else cluster_log.lambda <- log.lambda2
	}
	else cluster_log.lambda <- log.lambda2

	if(all((cluster_log.lambda == 0))) stop("There are no clusters! Try again changing the argument 'x' or 'K' or 'cluster.type'\n")

	log0 <- which(cluster_log.lambda == 0)
	if(length(log0) != 0){
		cluster_reg <- cluster_reg[-log0,,drop=FALSE]
		cluster_log.lambda <- cluster_log.lambda[-log0]
	}

	list(cluster_reg=cluster_reg,cluster_log.lambda=cluster_log.lambda)
}