# dudahart2: 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.valuep-value against null hypothesis of homogemeity.

dhratio of within-cluster sum of squares for two clusters and
overall sum of squares.

comparecritical value for `dh`

at level `alpha`

.

cluster1`FALSE`

if the null hypothesis of homogemeity is
rejected.

alphasee above.

z`1-alpha`

-quantile of a standard Gaussian.

## References

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

## Examples

# NOT RUN {
options(digits=2)
set.seed(98765)
iriss <- iris[sample(150,20),-5]
km <- kmeans(iriss,2)
dudahart2(iriss,km$cluster)
# }