consensus {agricolae}R Documentation

consensus of clusters

Description

The criterion of the consensus is to produce many trees by means of boostrap and to such calculate the relative frequency with members of the clusters.

Usage

consensus(data,distance=c("binary","euclidean","maximum","manhattan",
"canberra", "minkowski"),method=c("complete","ward","single","average",
"mcquitty","median", "centroid"),nboot=500,duplicate=TRUE,cex.text=1, 
col.text="red", ...)

Arguments

data data frame
distance method distance, see dist()
method method cluster, see hclust()
nboot The number of bootstrap samples desired.
duplicate control is TRUE other case is FALSE
cex.text size text on percentage consensus
col.text color text on percentage consensus
... parameters of the plot dendrogram

Details

distance: "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski". Method: "ward", "single", "complete", "average", "mcquitty", "median", "centroid". see functions: dist(), hclust().

Value

data numerical, the rownames is necesary'
nboot integer
duplicate logical TRUE or FALSE
cex.text size text on consensus
col.text color text on consensus

Author(s)

F. de Mendiburu

References

An Introduction to the Boostrap. Bradley Efron and Robert J. Tibshirani. 1993. Chapman and Hall/CRC

See Also

hclust, hgroups, hcut

Examples

library(agricolae)
data(pamCIP)
# only code
rownames(pamCIP)<-substr(rownames(pamCIP),1,6)
par(cex=0.8)
output<-consensus( pamCIP,distance="binary", method="complete",nboot=500)
# Order consensus
Groups<-output$table.dend[,c(6,5)]
Groups<-Groups[order(Groups[,2],decreasing=TRUE),]
print(Groups)
# Identification of the codes with the numbers.
cbind(output$dendrogram$labels)
# To reproduce dendrogram
dend<-output$dendrogram
data<-output$table.dend
plot(dend)
text(data[,3],data[,4],data[,5])

# Other examples
# classical dendrogram
dend<-as.dendrogram(output$dendrogram)
plot(dend,type="r",edgePar = list(lty=1:2, col=2:1))
text(data[,3],data[,4],data[,5],col="blue",cex=1)
#
plot(dend,type="t",edgePar = list(lty=1:2, col=2:1))
text(data[,3],data[,4],data[,5],col="blue",cex=1)
# Without the control of duplicates
output<-consensus( pamCIP,duplicate=FALSE,nboot=100)

[Package agricolae version 1.0-6 Index]