R: Diptest for discriminant coordinate projection

diptest.multi {fpc} | R Documentation

## Diptest for discriminant coordinate projection

### Description

Diptest (Hartigan and Hartigan, 1985, see `dip`) for data projected in discriminant coordinate separating optimally two class means (see `discrcoord`) as suggested by Tantrum, Murua and Stuetzle (2003).

### Usage

      diptest.multi(xdata,class,pvalue="uniform",M=100)

### Arguments

`xdata` | matrix. Potentially multidimensional dataset.
`class` | vector of integers giving class numbers for observations.
`pvalue` | `"uniform"` or `"tantrum"`. Defines whether the p-value is computed from a uniform null model as suggested in Hartigan and Hartigan (1985, using `dip.test`) or as suggested in Tantrum et al. (2003, using `dipp.tantrum`).
`M` | integer. Number of artificial datasets generated in order to estimate the p-value if `pvalue="tantrum"`.

### Value

The resulting p-value.

### Author(s)

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

### References

J. A. Hartigan and P. M. Hartigan (1985) The Dip Test of Unimodality, Annals of Statistics, 13, 70-84.

Tantrum, J., Murua, A. and Stuetzle, W. (2003) Assessment and Pruning of Hierarchical Model Based Clustering, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, Washington, D.C., 197-205.

### Examples

      require(diptest)
      x <- cbind(runif(100),runif(100))
      partition <- 1+(x[,1]<0.5)
      d1 <- diptest.multi(x,partition)
      d2 <- diptest.multi(x,partition,pvalue="tantrum",M=10)

[Package fpc version 2.1-10 Index]