Implements dendrogram seriation. Interface to DendSer.
dser(x,ser_weight,cost=costBAR, ...)# S3 method for data.frame
dser(x,ser_weight,cost=costBAR,...)
# S3 method for matrix
dser(x,ser_weight,cost=costBAR,scale=TRUE,dmethod="euclidean",...)
# S3 method for dist
dser(x,ser_weight,cost=costBAR,hmethod="average",...)
# S3 method for hclust
dser(x,ser_weight,cost=costBAR,...)
Used to select method.
Seriation weights. For cost=costLS, defaults to first column of matrix x, otherwise to symmetric matrix version of dist d.
Current choices are costLS, costPL, costLPL, costED, costARc, costBAR.
Logical value,controls whether matrix x should be scaled prior to forming dist.
Method of dist calculation. See function dist.
Method of hclust calculation. See function hclust.
Other args
Numeric vector giving an optimal dendrogram order
When x is a matrix or data.drame, forms a dist of rows using function dist with method = dmethod. When x is a dist, forms a hclust with method = hmethod which is then reordered.
# NOT RUN {
require(DendSer)
iriss <- scale(iris[,-5])
plotAsColor(iriss,order.row=dser(iriss))
w <- prcomp(iris[,-5],scale=TRUE)$x[,1]
h<- hclust(dist(iriss))
h$order <- ow <- dser(h,w,cost=costLS) # arranges cases along first PC, within dendrogram
# compare re-rordered dendrogram to PC scores, w
dev.new(width=10,height=5)
par(mar=c(0,2,1,1))
layout(matrix(1:2, nrow = 2), heights = c(4,1.5) )
par(cex=.7)
plot(h,main="",xlab="",hang=-1,labels=FALSE)
u <- par("usr")
par(mar=c(1,2,0,1))
plot.new()
par(usr=c(u[1:2],min(w),max(w)))
x<- 1:length(w)
rect(x-.5,0,x+.5,w[ow],col=cutree(h,3)[ow]+1)
# }
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