dser | R Documentation |
Implements dendrogram seriation. Interface to DendSer.
dser(x,ser_weight,cost=costBAR, ...) ## S3 method for class 'data.frame' dser(x,ser_weight,cost=costBAR,...) ## S3 method for class 'matrix' dser(x,ser_weight,cost=costBAR,scale=TRUE,dmethod="euclidean",...) ## S3 method for class 'dist' dser(x,ser_weight,cost=costBAR,hmethod="average",...) ## S3 method for class 'hclust' dser(x,ser_weight,cost=costBAR,...)
x |
Used to select method. |
ser_weight |
Seriation weights. For cost=costLS, defaults to first column of matrix x, otherwise to symmetric matrix version of dist d. |
cost |
Current choices are costLS, costPL, costLPL, costED, costARc, costBAR. |
scale |
Logical value,controls whether matrix x should be scaled prior to forming dist. |
dmethod |
Method of dist calculation. See function |
hmethod |
Method of hclust calculation. See function |
... |
Other args |
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.
Numeric vector giving an optimal dendrogram order
Catherine Hurley & Denise Earle
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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