R: Duda-Hart test for splitting

dudahart2 {fpc} | R Documentation

## Duda-Hart test for splitting

### Description

Duda-Hart test for whether a data set should be split into two clusters.

### Usage

      dudahart2(x,clustering,alpha=0.001)

### Arguments

`x` | data matrix or data frame.
`clustering` | vector of integers. Clustering into two clusters.
`alpha` | numeric between 0 and 1. Significance level (recommended to be small if this is used for estimating the number of clusters).

### Value

A list with components

`p.value` | p-value against null hypothesis of homogemeity.
`dh` | ratio of within-cluster sum of squares for two clusters and overall sum of squares.
`compare` | critical value for `dh` at level `alpha`.
`cluster1` | `FALSE` if the null hypothesis of homogemeity is rejected.
`alpha` | see above.
`z` | `1-alpha`-quantile of a standard Gaussian.

### Author(s)

Christian Hennig c.hennig@ucl.ac.uk http://www.homepages.ucl.ac.uk/~ucakche

### References

Duda, R. O. and Hart, P. E. (1973) Pattern Classification and Scene Analysis. Wiley, New York.

### See Also

`cluster.stats`

### Examples

      options(digits=2)
      set.seed(98765)
      iriss <- iris[sample(150,20),-5]
      km <- kmeans(iriss,2)
      dudahart2(iriss,km$cluster)

[Package fpc version 2.1-10 Index]