# consensus: consensus of clusters In agricolae: Statistical Procedures for Agricultural Research

 consensus 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", "gower","chisq"),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", "gower", "chisq". Method: "ward", "single", "complete", "average", "mcquitty", "median", "centroid". see functions: dist(), hclust() and daisy() of cluster.

### Value

 `table.dend ` The groups and consensus percentage `dendrogram` The class object is hclust, dendrogram plot `duplicate` Homonymous elements

F. de Mendiburu

### References

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

`hclust`, `hgroups`, `hcut`

### Examples

``````library(agricolae)
data(pamCIP)
# only code
rownames(pamCIP)<-substr(rownames(pamCIP),1,6)
output<-consensus( pamCIP,distance="binary", method="complete",nboot=5)
# 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=5)
## using distance gower, require cluster package.
# output<-consensus( pamCIP,distance="gower", method="complete",nboot=5)
``````

agricolae documentation built on Oct. 23, 2023, 1:06 a.m.