cophenetic {mva} | R Documentation |

## Cophenetic Distances for a Hierarchical Clustering

### Description

Computes the cophenetic distances for a hierarchical clustering.

### Usage

cophenetic(x)

### Arguments

### Details

The cophenetic distance between two observations that have been
clustered is defined to be the intergroup dissimilarity at which the
two observations are first combined into a single cluster.
Note that this distance has many ties and restrictions.

It can be argued that a dendrogram is an appropriate summary of some
data if the correlation between the original distances and the
cophenetic distances is high. Otherwise, it should simply be viewed as
the description of the output of the clustering algorithm.

### Value

An object of class `dist`

.

### Author(s)

Robert Gentleman

### References

Sneath, P.H.A. and Sokal, R.R (1973)
*Numerical Taxonomy: The Principles and Practice of Numerical
Classification*, p. 278 ff;
Freeman, San Francisco.

### See Also

`dist`

, `hclust`

### Examples

data(USArrests)
library(mva)
d1 <- dist(USArrests)
hc <- hclust(d1, "ave")
d2 <- cophenetic(hc)
cor(d1,d2) # 0.7659
## Example from Sneath & Sokal, Fig. 5-29, p.279
d0 <- c(1,3.8,4.4,5.1, 4,4.2,5, 2.6,5.3, 5.4)
attributes(d0) <- list(Size = 5, diag=TRUE)
class(d0) <- "dist"
names(d0) <- letters[1:5]
d0
str(upgma <- hclust(d0, method = "average"))
plot(upgma, hang = -1)
#
(d.coph <- cophenetic(upgma))
cor(d0, d.coph) # 0.9911